In [66]:
pip install pyarrow

Requirement already satisfied: pyarrow in c:\users\aleksas\anaconda3\lib\site-packages (6.0.0)
Requirement already satisfied: numpy>=1.16.6 in c:\users\aleksas\anaconda3\lib\site-packages (from pyarrow) (1.20.1)
Note: you may need to restart the kernel to use updated packages.
In [1]:
import pandas as pd
import numpy as np
In [4]:
parquet_file = 'C:\\...\\crypto_market\\1INCH-USDT.parquet'
failas = pd.read_parquet(parquet_file, engine='pyarrow')
failas.head(3)
Out[4]:
open high low close volume quote_asset_volume number_of_trades taker_buy_base_asset_volume taker_buy_quote_asset_volume
open_time
2020-12-25 05:00:00 0.200 2.900 0.2000 2.5000 619461.87500 1619167.500 1604 420214.5000 1.109962e+06
2020-12-25 05:01:00 2.500 2.500 2.2285 2.4231 436366.71875 1032071.875 1360 267897.2500 6.337132e+05
2020-12-25 05:02:00 2.423 2.699 2.4000 2.6989 388178.09375 976942.375 1093 254515.1875 6.439473e+05
In [5]:
# # pasalinti visi failai isskytus USDT


# import os, sys, glob, re

# def main():

#     mypath = "C:\\Users\\Aleksas\\baigiamasis_darbas\\crypto_market"
#     for root, dirs, files in os.walk(mypath):
#         for file in files:
#             p = os.path.join(root, file)
#             if os.path.isfile(p):
#                 if p[-13:] != "-USDT.parquet": 
#                     os.remove(p)
# main()
In [8]:
# prie kiekvieno failo pridetas stulpelis su failo pavadinimu


# path = "C:\\Users\\Aleksas\\baigiamasis_darbas\\crypto_market"
# files = os.listdir(path)

# df_total = pd.DataFrame()

# for file in files:
#     df_temp = pd.read_parquet(path + "\\" + file)
#     df_temp["filename"] = file
#     df_total = df_total.append(df_temp)
In [10]:
# import glob, os
# failas2 = glob.glob('C:\\Users\\Aleksas\\baigiamasis_darbas\\crypto_market\\*.parquet')
# print (failas2)
In [45]:
# Visi failai sujungti i viena faila


# df = pd.concat([pd.read_parquet(fp).assign(New=os.path.basename(fp)) for fp in failas2])
# print (df)
# df.to_parquet("crypto_market_remade")
In [11]:
parquet_file = 'crypto_market_remade'
failas = pd.read_parquet(parquet_file, engine='pyarrow')
failas
Out[11]:
open high low close volume quote_asset_volume number_of_trades taker_buy_base_asset_volume taker_buy_quote_asset_volume New
open_time
2020-12-25 05:00:00 0.2000 2.9000 0.2000 2.5000 619461.875000 1.619168e+06 1604 420214.500000 1.109962e+06 1INCH-USDT.parquet
2020-12-25 05:01:00 2.5000 2.5000 2.2285 2.4231 436366.718750 1.032072e+06 1360 267897.250000 6.337132e+05 1INCH-USDT.parquet
2020-12-25 05:02:00 2.4230 2.6990 2.4000 2.6989 388178.093750 9.769424e+05 1093 254515.187500 6.439473e+05 1INCH-USDT.parquet
2020-12-25 05:03:00 2.6989 2.7000 2.5681 2.6581 332343.906250 8.807702e+05 1187 198243.500000 5.262662e+05 1INCH-USDT.parquet
2020-12-25 05:04:00 2.6581 2.6600 2.5100 2.5500 189436.625000 4.899885e+05 1056 99868.500000 2.579790e+05 1INCH-USDT.parquet
... ... ... ... ... ... ... ... ... ... ...
2021-08-06 23:55:00 0.8898 0.8904 0.8898 0.8904 1123.719971 9.999978e+02 4 1123.719971 9.999978e+02 ZRX-USDT.parquet
2021-08-06 23:56:00 0.8900 0.8905 0.8900 0.8905 2918.750000 2.598726e+03 6 2918.750000 2.598726e+03 ZRX-USDT.parquet
2021-08-06 23:57:00 0.8915 0.8925 0.8915 0.8925 598.179993 5.337427e+02 9 416.549988 3.716822e+02 ZRX-USDT.parquet
2021-08-06 23:58:00 0.8925 0.8927 0.8916 0.8916 672.179993 5.998034e+02 10 423.279999 3.777836e+02 ZRX-USDT.parquet
2021-08-06 23:59:00 0.8916 0.8964 0.8916 0.8964 6568.890137 5.873960e+03 44 5882.310059 5.258752e+03 ZRX-USDT.parquet

162352212 rows × 10 columns

In [13]:
failas_tvarkytas = failas.drop(columns=['high', 'low', 'volume', 'quote_asset_volume', 'number_of_trades', 'taker_buy_base_asset_volume', 'taker_buy_quote_asset_volume'])
failas_tvarkytas
Out[13]:
open close New
open_time
2020-12-25 05:00:00 0.2000 2.5000 1INCH-USDT.parquet
2020-12-25 05:01:00 2.5000 2.4231 1INCH-USDT.parquet
2020-12-25 05:02:00 2.4230 2.6989 1INCH-USDT.parquet
2020-12-25 05:03:00 2.6989 2.6581 1INCH-USDT.parquet
2020-12-25 05:04:00 2.6581 2.5500 1INCH-USDT.parquet
... ... ... ...
2021-08-06 23:55:00 0.8898 0.8904 ZRX-USDT.parquet
2021-08-06 23:56:00 0.8900 0.8905 ZRX-USDT.parquet
2021-08-06 23:57:00 0.8915 0.8925 ZRX-USDT.parquet
2021-08-06 23:58:00 0.8925 0.8916 ZRX-USDT.parquet
2021-08-06 23:59:00 0.8916 0.8964 ZRX-USDT.parquet

162352212 rows × 3 columns

In [46]:
# failas_tvarkytas.reset_index(inplace=True)
# failas_tvarkytas
In [47]:
# failas_tvarkytas["date"] = failas_tvarkytas["open_time"]
# failas_tvarkytas
In [48]:
# failas_tvarkytas['date'] = failas_tvarkytas['date'].dt.date
# failas_tvarkytas
In [49]:
# failas_tvarkytas['new'] = failas_tvarkytas['New'] 
# failas_tvarkytas
In [21]:
# failas_tvarkytas.to_parquet("failas_6_stulpeliai")
In [3]:
crypto = pd.read_parquet("failas_6_stulpeliai")
crypto
Out[3]:
open_time open close date new
0 2020-12-25 05:00:00 0.2000 2.5000 2020-12-25 1INCH-USDT.parquet
1 2020-12-25 05:01:00 2.5000 2.4231 2020-12-25 1INCH-USDT.parquet
2 2020-12-25 05:02:00 2.4230 2.6989 2020-12-25 1INCH-USDT.parquet
3 2020-12-25 05:03:00 2.6989 2.6581 2020-12-25 1INCH-USDT.parquet
4 2020-12-25 05:04:00 2.6581 2.5500 2020-12-25 1INCH-USDT.parquet
... ... ... ... ... ...
162352207 2021-08-06 23:55:00 0.8898 0.8904 2021-08-06 ZRX-USDT.parquet
162352208 2021-08-06 23:56:00 0.8900 0.8905 2021-08-06 ZRX-USDT.parquet
162352209 2021-08-06 23:57:00 0.8915 0.8925 2021-08-06 ZRX-USDT.parquet
162352210 2021-08-06 23:58:00 0.8925 0.8916 2021-08-06 ZRX-USDT.parquet
162352211 2021-08-06 23:59:00 0.8916 0.8964 2021-08-06 ZRX-USDT.parquet

162352212 rows × 5 columns

In [50]:
# crypto = crypto.set_index("open_time")
# crypto
In [51]:
# crypto = crypto.assign(result=crypto['new'].str.replace(r'\.parquet', ''))
# crypto
In [52]:
# crypto["pair"] = crypto["result"]
# crypto
In [8]:
# del crypto['new']
In [9]:
# del crypto['result']
In [10]:
crypto
Out[10]:
open close date pair
open_time
2020-12-25 05:00:00 0.2000 2.5000 2020-12-25 1INCH-USDT
2020-12-25 05:01:00 2.5000 2.4231 2020-12-25 1INCH-USDT
2020-12-25 05:02:00 2.4230 2.6989 2020-12-25 1INCH-USDT
2020-12-25 05:03:00 2.6989 2.6581 2020-12-25 1INCH-USDT
2020-12-25 05:04:00 2.6581 2.5500 2020-12-25 1INCH-USDT
... ... ... ... ...
2021-08-06 23:55:00 0.8898 0.8904 2021-08-06 ZRX-USDT
2021-08-06 23:56:00 0.8900 0.8905 2021-08-06 ZRX-USDT
2021-08-06 23:57:00 0.8915 0.8925 2021-08-06 ZRX-USDT
2021-08-06 23:58:00 0.8925 0.8916 2021-08-06 ZRX-USDT
2021-08-06 23:59:00 0.8916 0.8964 2021-08-06 ZRX-USDT

162352212 rows × 4 columns

In [53]:
# crypto.reset_index(level=0, inplace=True)
# crypto
In [19]:
# crypto.loc[crypto.groupby(['date','pair']).open_time.idxmin()].to_parquet("crypto")
In [54]:
# crypto = pd.read_parquet("crypto")
# crypto
In [59]:
# crypto = crypto.sort_values(['pair','open_time'])
# crypto
In [58]:
# crypto["diff"] = crypto["open"].shift(-1)
# crypto["close"] = crypto["diff"]
# # del crypto['diff']
# crypto
In [57]:
# crypto["change_%"] = ((crypto["close"] / crypto["open"]) - 1)*100
# crypto
In [56]:
# # del crypto['open_time']
# crypto
In [55]:
# crypto['month'] = pd.to_datetime(crypto['date']).dt.to_period('M')
# crypto
In [16]:
# crypto = crypto.set_index("date")
In [21]:
crypto
Out[21]:
open close date pair change_% month
0 0.2000 2.2958 2020-12-25 1INCH-USDT 1047.900024 2020-12
1140 2.2958 1.5970 2020-12-26 1INCH-USDT -30.438190 2020-12
2580 1.5970 1.0600 2020-12-27 1INCH-USDT -33.625549 2020-12
4020 1.0600 1.1140 2020-12-28 1INCH-USDT 5.094337 2020-12
5460 1.1140 0.8845 2020-12-29 1INCH-USDT -20.601433 2020-12
... ... ... ... ... ... ...
162345012 0.7799 0.8162 2021-08-02 ZRX-USDT 4.654443 2021-08
162346452 0.8162 0.8589 2021-08-03 ZRX-USDT 5.231559 2021-08
162347892 0.8589 0.8704 2021-08-04 ZRX-USDT 1.338923 2021-08
162349332 0.8704 0.8888 2021-08-05 ZRX-USDT 2.113974 2021-08
162350772 0.8888 NaN 2021-08-06 ZRX-USDT NaN 2021-08

113102 rows × 6 columns

In [60]:
# crypto.groupby(["pair", "month"]).first()
In [61]:
# crypto_monthly = crypto.groupby(["pair", "month"]).first()
# crypto_monthly
In [28]:
# del crypto_monthly['date']
In [63]:
# crypto_monthly
In [62]:
# crypto_monthly["diff"] = crypto_monthly["open"].shift(-1)
# crypto_monthly
In [64]:
# crypto_monthly["close"] = crypto_monthly["diff"]
# crypto_monthly
In [34]:
#  del crypto_monthly['diff']
crypto_monthly
Out[34]:
open close change_%
pair month
1INCH-USDT 2020-12 0.2000 1.3623 1047.900024
2021-01 1.3623 4.9307 -15.429794
2021-02 4.9307 3.8408 1.768517
2021-03 3.8408 4.3422 7.253695
2021-04 4.3422 5.6389 2.565527
... ... ... ... ...
ZRX-USDT 2021-04 1.8822 1.8027 4.271591
2021-05 1.8027 1.0199 7.727301
2021-06 1.0199 0.7432 0.725567
2021-07 0.7432 0.8193 -7.333154
2021-08 0.8193 NaN -4.808980

3981 rows × 3 columns

In [65]:
# crypto_monthly["change_%"] = (crypto_monthly["close"] / crypto_monthly["open"] - 1) * 100
# crypto_monthly
In [50]:
# crypto_monthly = crypto_monthly.reset_index()
In [53]:
# crypto_monthly.to_parquet("crypto_monthly")
In [66]:
# crypto_monthly
In [56]:
crypto112 = crypto_monthly[crypto_monthly.month != "2021-08"]
crypto112
Out[56]:
pair month open close change_%
0 1INCH-USDT 2020-12 0.2000 1.3623 581.150024
1 1INCH-USDT 2021-01 1.3623 4.9307 261.939331
2 1INCH-USDT 2021-02 4.9307 3.8408 -22.104364
3 1INCH-USDT 2021-03 3.8408 4.3422 13.054562
4 1INCH-USDT 2021-04 4.3422 5.6389 29.862749
... ... ... ... ... ...
3975 ZRX-USDT 2021-03 1.2097 1.8822 55.592300
3976 ZRX-USDT 2021-04 1.8822 1.8027 -4.223776
3977 ZRX-USDT 2021-05 1.8027 1.0199 -43.423756
3978 ZRX-USDT 2021-06 1.0199 0.7432 -27.130110
3979 ZRX-USDT 2021-07 0.7432 0.8193 10.239506

3785 rows × 5 columns

In [58]:
import glob, os
In [61]:
# path = "C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv"
# files = os.listdir(path)

# df_total = pd.DataFrame()

# for file in files:
#     df_temp = pd.read_csv(path + "\\" + file)
#     df_temp["filename"] = file
#     df_total = df_total.append(df_temp)
In [62]:
failas3 = glob.glob('C:\\...\\baigiamasis_darbas\\stock_market\\sp500_csv\\*.csv')
print (failas3)

['C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\A.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AAL.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AAP.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AAPL.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ABBV.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ABC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ABMD.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ABT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ACN.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ADI.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ADM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ADP.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ADSK.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AEE.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AEP.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AIZ.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AJG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AKAM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ALB.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ALGN.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ALK.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ALLE.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ALTR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AMAT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AMD.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AME.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AMGN.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AMP.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AMT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AMZN.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ANET.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ANTM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AON.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AOS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\APA.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\APD.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\APH.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ARE.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ATVI.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AVB.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AVY.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AWK.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AXP.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\AZO.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BA.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BAC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BAX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BBY.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BDX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BEN.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BF-A.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BHI.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BIIB.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BIO.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BK.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BLK.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BMRA.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BMY.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BRK-A.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BSHI.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BSX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BWA.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\BXP.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\C.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CAG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CAH.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CAT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CB.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CCI.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CDE.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CDNS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CF.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CFG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CHD.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CHRW.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CHTR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CINF.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CL.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CLX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CME.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CMG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CMI.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CNC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CNP.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CNWT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\COG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\COO.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\COP.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\COST.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\COTY.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\COWN.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CPB.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CPICQ.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CPRT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CRM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CSCO.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CTAS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CTQ.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CTSH.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CTXS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\CUK.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\D.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\DAL.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\DE.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\DFS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\DG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\DGX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\DHI.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\DIS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\DLTR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\DOV.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\DPZ.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\DRE.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\DRI.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\DTE.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\DVA.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\DXCM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\EA.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\EBAY.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ECL.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ED.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\EFX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\EIX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\EL.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\EMN.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\EMR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ENS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\EOG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\EQIX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\EQR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ES.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ESS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\EW.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\EXR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\F.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FANG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FAST.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FB.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FBHS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FCGN.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FCX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FDX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FE.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FFIV.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FIS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FISV.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FITB.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FLS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FLT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FMBM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FMC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FN.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FPLPF.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FRC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FRMC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FRT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\FTI.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\GD.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\GE.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\GGG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\GILD.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\GIS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\GM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\GOOG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\GPC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\GPN.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\GRMN.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\GS-PJ.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\GWW.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HAL.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HAS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HBAN.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HBI.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HCA.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HD.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HES.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HFC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HII.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HLT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HOLX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HON.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HPE.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HPQ.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HRB.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HRL.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HSIC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HST.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HSY.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HTLF.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\HUM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\IBM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ICE.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\IDXX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\IEX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\IFF.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\IFGNF.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ILMN.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\INTH.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\INTU.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\IP.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\IPGP.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\IR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\IRM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ISRG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\IT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ITW.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\IVZ.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\JBHT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\JCI.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\JKHY.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\JNJ.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\JNPR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\JPM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\K.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\KACPF.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\KEY.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\KEYS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\KGNR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\KHC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\KIM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\KMB.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\KMX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\KO.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\KR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\KRA.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\KSS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\KSU.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\LBTYA.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\LDOS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\LEG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\LH.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\LKQ.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\LMT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\LNC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\LNT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\LOW.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\LRCX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\LUV.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\LVS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\LYB.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\LYV.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MAA.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MAR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MCD.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MCHP.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MCK.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MCO.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MDLZ.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MDT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MET.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MGM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MHK.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MKTX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MLM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MMC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MMM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MNST.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MO.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MOS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MPC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MRCR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MRK.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MRO.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MS-PF.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MSCI.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MSFT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MSI.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MU.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\MXIM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NCLH.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NCTKF.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NDAQ.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NEE.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NEOG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NFLX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NI.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NLSN.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NMHLY.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NOC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NOK.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NOV.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NOW.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NOXL.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NRG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NSC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NTAP.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NTRA.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NTRR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NTRS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NVR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NVRO.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\NWL.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\O.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ODFL.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\OKE.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\OMC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ORBC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ORLY.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\OXY.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PAYX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PBCT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PCAR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PEG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PEP.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PFE.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PH.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PHM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PKG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PKI.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PLD.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PNR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PNW.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PNWRF.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PPG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PRU.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PSX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PVH.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PWR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\PXD.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\QRVO.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\RCL.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\RE.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\REG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\REGN.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\RF.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\RHI.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\RIBT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\RJF.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\RL.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\RLI.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\RMD.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ROK.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ROL.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ROP.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ROST.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\RSG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\RSNHF.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\RXMD.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\SBUX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\SCHW.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\SEE.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\SEGXF.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\SHW.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\SIVB.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\SLB.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\SLG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\SNPS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\SO.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\SONC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\SPG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\SRE.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\SRG.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\STT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\STX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\STZ-B.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\SWK.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\SWKS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\SYF.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\SYK.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\T.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\TAP.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\TCYSF.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\TEL.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\TJX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\TMO.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\TMUS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\TRAUF.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\TROW.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\TRV.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\TSCO.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\TSN.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\TTWO.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\TW.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\TWTR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\TXN.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\TXT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\TYL.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\UA.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\UAL.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\UDR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\UEEC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\UHS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ULTA.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\UNM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\UNP.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\UPS.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\URI.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\USB.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\V.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\VFC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\VMC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\VNO-PK.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\VRSK.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\VRSN.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\VTR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\VZ.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\WAT.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\WBA.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\WDC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\WEC.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\WHR.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\WM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\WMB.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\WRB.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\WRK.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\WSPOF.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\WST.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\WU.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\WY.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\WYNN.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\XEL.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\XLEFF.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\XLNX.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\XOM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\XYL.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\YUM.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ZBH.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ZION.csv', 'C:\\Users\\Aleksas\\baigiamasis_darbas\\stock_market\\sp500_csv\\ZTS.csv']
In [64]:
stock_market_sp500 = pd.concat([pd.read_csv(fp).assign(New=os.path.basename(fp)) for fp in failas3])
print (stock_market_sp500)
stock_market_sp500.to_csv("stock_market_sp500")

            Date         Low        Open      Volume        High       Close  \
0     18-11-1999   28.612303   32.546494  62546380.0   35.765381   31.473534   
1     19-11-1999   28.478184   30.713518  15234146.0   30.758226   28.880545   
2     22-11-1999   28.657009   29.551144   6577870.0   31.473534   31.473534   
3     23-11-1999   28.612303   30.400572   5975611.0   31.205294   28.612303   
4     24-11-1999   28.612303   28.701717   4843231.0   29.998213   29.372318   
...          ...         ...         ...         ...         ...         ...   
2195  20-10-2021  204.839996  205.850006    794700.0  206.610001  206.309998   
2196  21-10-2021  205.309998  207.080002    957000.0  208.779999  208.619995   
2197  22-10-2021  206.839996  208.029999   1104400.0  209.080002  208.509995   
2198  25-10-2021  207.100006  208.809998   1224700.0  211.770004  211.520004   
2199  26-10-2021  207.994995  211.000000   1188862.0  211.740005  210.520004   

      Adjusted Close      New  
0          27.102226    A.csv  
1          24.869373    A.csv  
2          27.102226    A.csv  
3          24.638388    A.csv  
4          25.292839    A.csv  
...              ...      ...  
2195      206.309998  ZTS.csv  
2196      208.619995  ZTS.csv  
2197      208.509995  ZTS.csv  
2198      211.520004  ZTS.csv  
2199      210.520004  ZTS.csv  

[3225048 rows x 8 columns]
In [213]:
import os, sys, glob, re
csv_file = 'stock_market_sp500'
failas_sp500 = pd.read_csv(csv_file)
failas_sp500
Out[213]:
Unnamed: 0 Date Low Open Volume High Close Adjusted Close New
0 0 18-11-1999 28.612303 32.546494 62546380.0 35.765381 31.473534 27.102226 A.csv
1 1 19-11-1999 28.478184 30.713518 15234146.0 30.758226 28.880545 24.869373 A.csv
2 2 22-11-1999 28.657009 29.551144 6577870.0 31.473534 31.473534 27.102226 A.csv
3 3 23-11-1999 28.612303 30.400572 5975611.0 31.205294 28.612303 24.638388 A.csv
4 4 24-11-1999 28.612303 28.701717 4843231.0 29.998213 29.372318 25.292839 A.csv
... ... ... ... ... ... ... ... ... ...
3225043 2195 20-10-2021 204.839996 205.850006 794700.0 206.610001 206.309998 206.309998 ZTS.csv
3225044 2196 21-10-2021 205.309998 207.080002 957000.0 208.779999 208.619995 208.619995 ZTS.csv
3225045 2197 22-10-2021 206.839996 208.029999 1104400.0 209.080002 208.509995 208.509995 ZTS.csv
3225046 2198 25-10-2021 207.100006 208.809998 1224700.0 211.770004 211.520004 211.520004 ZTS.csv
3225047 2199 26-10-2021 207.994995 211.000000 1188862.0 211.740005 210.520004 210.520004 ZTS.csv

3225048 rows × 9 columns

In [214]:
failas_sp500 = failas_sp500.drop(columns=['Unnamed: 0', 'Low', 'Volume', 'High', 'Adjusted Close'])
failas_sp500
Out[214]:
Date Open Close New
0 18-11-1999 32.546494 31.473534 A.csv
1 19-11-1999 30.713518 28.880545 A.csv
2 22-11-1999 29.551144 31.473534 A.csv
3 23-11-1999 30.400572 28.612303 A.csv
4 24-11-1999 28.701717 29.372318 A.csv
... ... ... ... ...
3225043 20-10-2021 205.850006 206.309998 ZTS.csv
3225044 21-10-2021 207.080002 208.619995 ZTS.csv
3225045 22-10-2021 208.029999 208.509995 ZTS.csv
3225046 25-10-2021 208.809998 211.520004 ZTS.csv
3225047 26-10-2021 211.000000 210.520004 ZTS.csv

3225048 rows × 4 columns

In [215]:
stocks = failas_sp500.assign(result=failas_sp500['New'].str.replace(r'\.csv', ''))
stocks

<ipython-input-215-b253abf27042>:1: FutureWarning: The default value of regex will change from True to False in a future version.
  stocks = failas_sp500.assign(result=failas_sp500['New'].str.replace(r'\.csv', ''))
Out[215]:
Date Open Close New result
0 18-11-1999 32.546494 31.473534 A.csv A
1 19-11-1999 30.713518 28.880545 A.csv A
2 22-11-1999 29.551144 31.473534 A.csv A
3 23-11-1999 30.400572 28.612303 A.csv A
4 24-11-1999 28.701717 29.372318 A.csv A
... ... ... ... ... ...
3225043 20-10-2021 205.850006 206.309998 ZTS.csv ZTS
3225044 21-10-2021 207.080002 208.619995 ZTS.csv ZTS
3225045 22-10-2021 208.029999 208.509995 ZTS.csv ZTS
3225046 25-10-2021 208.809998 211.520004 ZTS.csv ZTS
3225047 26-10-2021 211.000000 210.520004 ZTS.csv ZTS

3225048 rows × 5 columns

In [216]:
# del stocks['New']
stocks.rename({'result': 'stock', 'Date': 'date', 'Open': 'open', 'Close': 'close',}, axis=1, inplace=True)
stocks
Out[216]:
date open close New stock
0 18-11-1999 32.546494 31.473534 A.csv A
1 19-11-1999 30.713518 28.880545 A.csv A
2 22-11-1999 29.551144 31.473534 A.csv A
3 23-11-1999 30.400572 28.612303 A.csv A
4 24-11-1999 28.701717 29.372318 A.csv A
... ... ... ... ... ...
3225043 20-10-2021 205.850006 206.309998 ZTS.csv ZTS
3225044 21-10-2021 207.080002 208.619995 ZTS.csv ZTS
3225045 22-10-2021 208.029999 208.509995 ZTS.csv ZTS
3225046 25-10-2021 208.809998 211.520004 ZTS.csv ZTS
3225047 26-10-2021 211.000000 210.520004 ZTS.csv ZTS

3225048 rows × 5 columns

In [217]:
stocks['month'] = pd.to_datetime(stocks['date']).dt.to_period('M')
stocks
Out[217]:
date open close New stock month
0 18-11-1999 32.546494 31.473534 A.csv A 1999-11
1 19-11-1999 30.713518 28.880545 A.csv A 1999-11
2 22-11-1999 29.551144 31.473534 A.csv A 1999-11
3 23-11-1999 30.400572 28.612303 A.csv A 1999-11
4 24-11-1999 28.701717 29.372318 A.csv A 1999-11
... ... ... ... ... ... ...
3225043 20-10-2021 205.850006 206.309998 ZTS.csv ZTS 2021-10
3225044 21-10-2021 207.080002 208.619995 ZTS.csv ZTS 2021-10
3225045 22-10-2021 208.029999 208.509995 ZTS.csv ZTS 2021-10
3225046 25-10-2021 208.809998 211.520004 ZTS.csv ZTS 2021-10
3225047 26-10-2021 211.000000 210.520004 ZTS.csv ZTS 2021-10

3225048 rows × 6 columns

In [218]:
# stocks_monthly = stocks.groupby(["stock", "month"]).first()
# stocks_monthly
stocks['year'] = pd.to_datetime(stocks['date']).dt.to_period('Y')
stocks
Out[218]:
date open close New stock month year
0 18-11-1999 32.546494 31.473534 A.csv A 1999-11 1999
1 19-11-1999 30.713518 28.880545 A.csv A 1999-11 1999
2 22-11-1999 29.551144 31.473534 A.csv A 1999-11 1999
3 23-11-1999 30.400572 28.612303 A.csv A 1999-11 1999
4 24-11-1999 28.701717 29.372318 A.csv A 1999-11 1999
... ... ... ... ... ... ... ...
3225043 20-10-2021 205.850006 206.309998 ZTS.csv ZTS 2021-10 2021
3225044 21-10-2021 207.080002 208.619995 ZTS.csv ZTS 2021-10 2021
3225045 22-10-2021 208.029999 208.509995 ZTS.csv ZTS 2021-10 2021
3225046 25-10-2021 208.809998 211.520004 ZTS.csv ZTS 2021-10 2021
3225047 26-10-2021 211.000000 210.520004 ZTS.csv ZTS 2021-10 2021

3225048 rows × 7 columns

In [237]:
stocks = stocks[stocks.year != "2016"]
stocks
Out[237]:
date open close New stock month year
4307 03-01-2017 45.930000 46.490002 A.csv A 2017-03 2017
4308 04-01-2017 46.930000 47.099998 A.csv A 2017-04 2017
4309 05-01-2017 47.049999 46.540001 A.csv A 2017-05 2017
4310 06-01-2017 46.630001 47.990002 A.csv A 2017-06 2017
4311 09-01-2017 48.009998 48.139999 A.csv A 2017-09 2017
... ... ... ... ... ... ... ...
3225043 20-10-2021 205.850006 206.309998 ZTS.csv ZTS 2021-10 2021
3225044 21-10-2021 207.080002 208.619995 ZTS.csv ZTS 2021-10 2021
3225045 22-10-2021 208.029999 208.509995 ZTS.csv ZTS 2021-10 2021
3225046 25-10-2021 208.809998 211.520004 ZTS.csv ZTS 2021-10 2021
3225047 26-10-2021 211.000000 210.520004 ZTS.csv ZTS 2021-10 2021

1618269 rows × 7 columns

In [238]:
# del stocks["New"]
# del stocks["year"]
stocks
Out[238]:
date open close stock month
4307 03-01-2017 45.930000 46.490002 A 2017-03
4308 04-01-2017 46.930000 47.099998 A 2017-04
4309 05-01-2017 47.049999 46.540001 A 2017-05
4310 06-01-2017 46.630001 47.990002 A 2017-06
4311 09-01-2017 48.009998 48.139999 A 2017-09
... ... ... ... ... ...
3225043 20-10-2021 205.850006 206.309998 ZTS 2021-10
3225044 21-10-2021 207.080002 208.619995 ZTS 2021-10
3225045 22-10-2021 208.029999 208.509995 ZTS 2021-10
3225046 25-10-2021 208.809998 211.520004 ZTS 2021-10
3225047 26-10-2021 211.000000 210.520004 ZTS 2021-10

1618269 rows × 5 columns

In [242]:
stocks = stocks.groupby(["stock", "month"]).first()
stocks
Out[242]:
date open close
stock month
A 2017-01 13-01-2017 48.599998 48.689999
2017-02 02-02-2017 48.880001 48.900002
2017-03 03-01-2017 45.930000 46.490002
2017-04 04-01-2017 46.930000 47.099998
2017-05 05-01-2017 47.049999 46.540001
... ... ... ... ...
ZTS 2021-08 08-01-2021 167.399994 168.110001
2021-09 09-02-2021 159.809998 159.830002
2021-10 10-02-2021 161.250000 160.619995
2021-11 11-01-2021 167.899994 169.389999
2021-12 12-01-2021 169.020004 166.119995

78943 rows × 3 columns

In [244]:
# stocks = stocks[stocks.month != "2021-12"]
stocks.reset_index()
Out[244]:
stock month date open close
0 A 2017-01 13-01-2017 48.599998 48.689999
1 A 2017-02 02-02-2017 48.880001 48.900002
2 A 2017-03 03-01-2017 45.930000 46.490002
3 A 2017-04 04-01-2017 46.930000 47.099998
4 A 2017-05 05-01-2017 47.049999 46.540001
... ... ... ... ... ...
78938 ZTS 2021-08 08-01-2021 167.399994 168.110001
78939 ZTS 2021-09 09-02-2021 159.809998 159.830002
78940 ZTS 2021-10 10-02-2021 161.250000 160.619995
78941 ZTS 2021-11 11-01-2021 167.899994 169.389999
78942 ZTS 2021-12 12-01-2021 169.020004 166.119995

78943 rows × 5 columns

In [247]:
stocks["diff"] = stocks["open"].shift(-1)
stocks
Out[247]:
date open close diff
stock month
A 2017-01 13-01-2017 48.599998 48.689999 48.880001
2017-02 02-02-2017 48.880001 48.900002 45.930000
2017-03 03-01-2017 45.930000 46.490002 46.930000
2017-04 04-01-2017 46.930000 47.099998 47.049999
2017-05 05-01-2017 47.049999 46.540001 46.630001
... ... ... ... ... ...
ZTS 2021-08 08-01-2021 167.399994 168.110001 159.809998
2021-09 09-02-2021 159.809998 159.830002 161.250000
2021-10 10-02-2021 161.250000 160.619995 167.899994
2021-11 11-01-2021 167.899994 169.389999 169.020004
2021-12 12-01-2021 169.020004 166.119995 NaN

78943 rows × 4 columns

In [248]:
stocks["close"] = stocks["diff"]
stocks
Out[248]:
date open close diff
stock month
A 2017-01 13-01-2017 48.599998 48.880001 48.880001
2017-02 02-02-2017 48.880001 45.930000 45.930000
2017-03 03-01-2017 45.930000 46.930000 46.930000
2017-04 04-01-2017 46.930000 47.049999 47.049999
2017-05 05-01-2017 47.049999 46.630001 46.630001
... ... ... ... ... ...
ZTS 2021-08 08-01-2021 167.399994 159.809998 159.809998
2021-09 09-02-2021 159.809998 161.250000 161.250000
2021-10 10-02-2021 161.250000 167.899994 167.899994
2021-11 11-01-2021 167.899994 169.020004 169.020004
2021-12 12-01-2021 169.020004 NaN NaN

78943 rows × 4 columns

In [249]:
# del stocks['diff']
In [250]:
stocks
Out[250]:
date open close
stock month
A 2017-01 13-01-2017 48.599998 48.880001
2017-02 02-02-2017 48.880001 45.930000
2017-03 03-01-2017 45.930000 46.930000
2017-04 04-01-2017 46.930000 47.049999
2017-05 05-01-2017 47.049999 46.630001
... ... ... ... ...
ZTS 2021-08 08-01-2021 167.399994 159.809998
2021-09 09-02-2021 159.809998 161.250000
2021-10 10-02-2021 161.250000 167.899994
2021-11 11-01-2021 167.899994 169.020004
2021-12 12-01-2021 169.020004 NaN

78943 rows × 3 columns

In [251]:
stocks["change_%"] = (stocks["close"] / stocks ["open"] - 1) * 100
In [252]:
stocks
Out[252]:
date open close change_%
stock month
A 2017-01 13-01-2017 48.599998 48.880001 0.576137
2017-02 02-02-2017 48.880001 45.930000 -6.035190
2017-03 03-01-2017 45.930000 46.930000 2.177226
2017-04 04-01-2017 46.930000 47.049999 0.255698
2017-05 05-01-2017 47.049999 46.630001 -0.892663
... ... ... ... ... ...
ZTS 2021-08 08-01-2021 167.399994 159.809998 -4.534048
2021-09 09-02-2021 159.809998 161.250000 0.901072
2021-10 10-02-2021 161.250000 167.899994 4.124027
2021-11 11-01-2021 167.899994 169.020004 0.667070
2021-12 12-01-2021 169.020004 NaN NaN

78943 rows × 4 columns

In [253]:
stocks = stocks.reset_index()
stocks
Out[253]:
stock month date open close change_%
0 A 2017-01 13-01-2017 48.599998 48.880001 0.576137
1 A 2017-02 02-02-2017 48.880001 45.930000 -6.035190
2 A 2017-03 03-01-2017 45.930000 46.930000 2.177226
3 A 2017-04 04-01-2017 46.930000 47.049999 0.255698
4 A 2017-05 05-01-2017 47.049999 46.630001 -0.892663
... ... ... ... ... ... ...
78938 ZTS 2021-08 08-01-2021 167.399994 159.809998 -4.534048
78939 ZTS 2021-09 09-02-2021 159.809998 161.250000 0.901072
78940 ZTS 2021-10 10-02-2021 161.250000 167.899994 4.124027
78941 ZTS 2021-11 11-01-2021 167.899994 169.020004 0.667070
78942 ZTS 2021-12 12-01-2021 169.020004 NaN NaN

78943 rows × 6 columns

In [258]:
# stocks = stocks[stocks.month != "2021-08"]
stocks
Out[258]:
stock month date open close change_%
0 A 2017-01 13-01-2017 48.599998 48.880001 0.576137
1 A 2017-02 02-02-2017 48.880001 45.930000 -6.035190
2 A 2017-03 03-01-2017 45.930000 46.930000 2.177226
3 A 2017-04 04-01-2017 46.930000 47.049999 0.255698
4 A 2017-05 05-01-2017 47.049999 46.630001 -0.892663
... ... ... ... ... ... ...
78933 ZTS 2021-03 03-02-2021 157.320007 166.000000 5.517412
78934 ZTS 2021-04 04-01-2021 166.000000 163.149994 -1.716871
78935 ZTS 2021-05 05-01-2021 163.149994 162.919998 -0.140972
78936 ZTS 2021-06 06-01-2021 162.919998 167.449997 2.780505
78937 ZTS 2021-07 07-01-2021 167.449997 167.399994 -0.029861

76833 rows × 6 columns

In [261]:
crypto112.to_csv("crypto_final")
In [262]:
crypto112
Out[262]:
pair month open close change_%
0 1INCH-USDT 2020-12 0.2000 1.3623 581.150024
1 1INCH-USDT 2021-01 1.3623 4.9307 261.939331
2 1INCH-USDT 2021-02 4.9307 3.8408 -22.104364
3 1INCH-USDT 2021-03 3.8408 4.3422 13.054562
4 1INCH-USDT 2021-04 4.3422 5.6389 29.862749
... ... ... ... ... ...
3975 ZRX-USDT 2021-03 1.2097 1.8822 55.592300
3976 ZRX-USDT 2021-04 1.8822 1.8027 -4.223776
3977 ZRX-USDT 2021-05 1.8027 1.0199 -43.423756
3978 ZRX-USDT 2021-06 1.0199 0.7432 -27.130110
3979 ZRX-USDT 2021-07 0.7432 0.8193 10.239506

3785 rows × 5 columns

In [264]:
# del stocks["date"]
In [265]:
stocks
Out[265]:
stock month open close change_%
0 A 2017-01 48.599998 48.880001 0.576137
1 A 2017-02 48.880001 45.930000 -6.035190
2 A 2017-03 45.930000 46.930000 2.177226
3 A 2017-04 46.930000 47.049999 0.255698
4 A 2017-05 47.049999 46.630001 -0.892663
... ... ... ... ... ...
78933 ZTS 2021-03 157.320007 166.000000 5.517412
78934 ZTS 2021-04 166.000000 163.149994 -1.716871
78935 ZTS 2021-05 163.149994 162.919998 -0.140972
78936 ZTS 2021-06 162.919998 167.449997 2.780505
78937 ZTS 2021-07 167.449997 167.399994 -0.029861

76833 rows × 5 columns

In [ ]:
In [267]:
stocks.to_csv("stocks_final")
In [ ]:
In [ ]:
In [ ]:
In [ ]:
In [ ]:
In [ ]:
In [ ]:
In [ ]:
In [ ]:
In [ ]: