Issue
CODE:-
from datetime import date
from datetime import timedelta
from nsepy import get_history
import pandas as pd
end1 = date.today()
start1 = end1 - timedelta(days=25)
exp_date1 = date(2022,8,25)
exp_date2 = date(2022,9,29)
# stock = ['HDFCLIFE']
stock = ['RELIANCE','HDFCBANK','INFY','ICICIBANK','HDFC','TCS','KOTAKBANK','LT','SBIN','HINDUNILVR','AXISBANK',
'ITC','BAJFINANCE','BHARTIARTL','ASIANPAINT','HCLTECH','MARUTI','TITAN','BAJAJFINSV','TATAMOTORS',
'TECHM','SUNPHARMA','TATASTEEL','M&M','WIPRO','ULTRACEMCO','POWERGRID','HINDALCO','NTPC','NESTLEIND',
'GRASIM','ONGC','JSWSTEEL','HDFCLIFE','INDUSINDBK','SBILIFE','DRREDDY','ADANIPORTS','DIVISLAB','CIPLA',
'BAJAJ-AUTO','TATACONSUM','UPL','BRITANNIA','BPCL','EICHERMOT','HEROMOTOCO','COALINDIA','SHREECEM','IOC']
target_stocks = []
# oi_change = []
for stock in stock:
stock_jan = get_history(symbol=stock,
start=start1,
end=end1,
futures=True,
expiry_date=exp_date1)
stock_feb = get_history(symbol=stock,
start=start1,
end=end1,
futures=True,
expiry_date=exp_date2)
delivery_per_age = get_history(symbol=stock,
start=start1,
end=end1)
symbol_s = get_history(symbol=stock,
start=start1,
end=end1)
oi_combined = pd.concat([stock_jan['Change in OI'] + stock_feb['Change in OI']])
total_oi = pd.concat([stock_jan['Open Interest']+stock_feb['Open Interest']])
delivery_vol = pd.concat([delivery_per_age['Deliverable Volume']])
# delivery_per = pd.concat([delivery_per_age['%Deliverble']*100])
na_me = pd.concat([symbol_s['Symbol']])
close = pd.concat([delivery_per_age['Close']])
df = pd.DataFrame(na_me)
df['TOTAL_OPN_INT'] = total_oi
df['OI_COMBINED'] = oi_combined
df['%_CHANGE'] = ((df['OI_COMBINED'] / df['TOTAL_OPN_INT']) * 100).__round__(2)
df['AVG_OI_COMBINED'] = df['OI_COMBINED'].rolling(5).mean()
# df['DELIVERY_VOL'] = delivery_vol
# df['AVG_DELIVERY_VOL'] = df['DELIVERY_VOL'].rolling(5).mean()
# df['DELIVERY_PER'] = delivery_per
# df['AVG_DELIVERY_%'] = df['DELIVERY_PER'].rolling(5).mean()
df['_CLOSE_PRICE_'] = close
pd.set_option('display.max_columns',8)
pd.set_option('display.width',200)
# print(df)
cond = ((df.loc[df.index[-5:-1], '%_CHANGE'].agg(min) > 0) |(df.loc[df.index[-6:-1], '%_CHANGE'].agg(min) > 0)) & (df.loc[df.index[-1], '%_CHANGE'] < 0)
if(cond):
target_stocks.append(df)
print(target_stocks)
OUTPUT:-
From above code I am getting the output for the day 11-aug-2022 which is displayed below.
[ Symbol TOTAL_OPN_INT OI_COMBINED %_CHANGE AVG_OI_COMBINED _CLOSE_PRICE_
Date
2022-07-18 EICHERMOT 489650 61250 12.51 NaN 3036.50
2022-07-19 EICHERMOT 547400 57750 10.55 NaN 3077.70
2022-07-20 EICHERMOT 556150 8750 1.57 NaN 3045.00
2022-07-21 EICHERMOT 572250 16100 2.81 NaN 3081.20
2022-07-22 EICHERMOT 728000 155750 21.39 59920.0 3147.60
2022-07-25 EICHERMOT 1358700 630700 46.42 173810.0 3086.70
2022-07-26 EICHERMOT 1789900 431200 24.09 248500.0 3023.30
2022-07-27 EICHERMOT 2226700 436800 19.62 334110.0 3057.40
2022-07-28 EICHERMOT 2843750 617050 21.70 454300.0 3054.00
2022-07-29 EICHERMOT 2878400 34650 1.20 430080.0 3093.45
2022-08-01 EICHERMOT 3047100 168700 5.54 337680.0 3088.40
2022-08-02 EICHERMOT 3491250 444150 12.72 340270.0 3120.95
2022-08-03 EICHERMOT 3871700 380450 9.83 329000.0 3138.20
2022-08-04 EICHERMOT 3943100 71400 1.81 219870.0 3145.80
2022-08-05 EICHERMOT 4058950 115850 2.85 236110.0 3089.60
2022-08-08 EICHERMOT 4060000 1050 0.03 202580.0 3116.75
2022-08-10 EICHERMOT 4165000 105000 2.52 134750.0 3154.55
2022-08-11 EICHERMOT 3880450 -284550 -7.33 1750.0 3176.45, Symbol TOTAL_OPN_INT OI_COMBINED %_CHANGE AVG_OI_COMBINED _CLOSE_PRICE_
Date
2022-07-18 COALINDIA 7631400 1965600 25.76 NaN 195.60
2022-07-19 COALINDIA 8400000 768600 9.15 NaN 198.25
2022-07-20 COALINDIA 9361800 961800 10.27 NaN 197.85
2022-07-21 COALINDIA 10042200 680400 6.78 NaN 198.60
2022-07-22 COALINDIA 11020800 978600 8.88 1071000.0 197.10
2022-07-25 COALINDIA 18131400 7110600 39.22 2100000.0 200.90
2022-07-26 COALINDIA 25368000 7236600 28.53 3393600.0 202.30
2022-07-27 COALINDIA 29454600 4086600 13.87 4018560.0 203.45
2022-07-28 COALINDIA 31941000 2486400 7.78 4379760.0 202.85
2022-07-29 COALINDIA 33121200 1180200 3.56 4420080.0 211.25
2022-08-01 COALINDIA 32928000 -193200 -0.59 2959320.0 212.75
2022-08-02 COALINDIA 33398400 470400 1.41 1606080.0 215.25
2022-08-03 COALINDIA 32646600 -751800 -2.30 638400.0 212.10
2022-08-04 COALINDIA 33734400 1087800 3.22 358680.0 207.15
2022-08-05 COALINDIA 33780600 46200 0.14 131880.0 208.45
2022-08-08 COALINDIA 37044000 3263400 8.81 823200.0 215.40
2022-08-10 COALINDIA 38186400 1142400 2.99 957600.0 219.85
2022-08-11 COALINDIA 35653800 -2532600 -7.10 601440.0 218.60, Symbol TOTAL_OPN_INT OI_COMBINED %_CHANGE AVG_OI_COMBINED _CLOSE_PRICE_
Date
2022-07-18 SHREECEM 30675 2850 9.29 NaN 20055.70
2022-07-19 SHREECEM 34800 4125 11.85 NaN 20068.20
2022-07-20 SHREECEM 38250 3450 9.02 NaN 20208.20
2022-07-21 SHREECEM 41800 3550 8.49 NaN 20442.95
2022-07-22 SHREECEM 58250 16450 28.24 6085.0 20780.00
2022-07-25 SHREECEM 118700 60450 50.93 17605.0 20679.05
2022-07-26 SHREECEM 194375 75675 38.93 31915.0 20652.35
2022-07-27 SHREECEM 241500 47125 19.51 40650.0 21023.50
2022-07-28 SHREECEM 285400 43900 15.38 48720.0 20415.45
2022-07-29 SHREECEM 294975 9575 3.25 47345.0 20498.00
2022-08-01 SHREECEM 295275 300 0.10 35315.0 20947.00
2022-08-02 SHREECEM 297050 1775 0.60 20535.0 21110.95
2022-08-03 SHREECEM 303500 6450 2.13 12400.0 20956.45
2022-08-04 SHREECEM 319375 15875 4.97 6795.0 20687.90
2022-08-05 SHREECEM 322725 3350 1.04 5550.0 21237.40
2022-08-08 SHREECEM 327450 4725 1.44 6435.0 21195.60
2022-08-10 SHREECEM 333275 5825 1.75 7245.0 21104.90
2022-08-11 SHREECEM 332225 -1050 -0.32 5745.0 21192.95]
Now when I run the code I am getting this output. How to load this output into the excel as .csv file with the name as '11-08-2022.csv'. And suppose if I run the code on 12-08-2022 then another .csv file should add in the same folder where first .csv file has saved and now the file name should be 12-08-2022......in this way when I run the code each time there should be one .csv file created with the name as todays date.
thank you.
Solution
first import libraries
import pandas as pd
import datetime
to load data from csv file
df = pd.read_csv('file_path')
example
df = pd.read_csv('/content/sample_data/california_housing_test.csv')
to save data to csv file
df.to_csv('file_name')
file will be saved to your current directory
to save some other folder
df.to_csv('absolute_path/file_name.csv')
example
df2.to_csv('/content/drive/MyDrive/some_folder/modified_df.csv')
in your case, you want something like this
file_name = f'{datetime.datetime.now().day}-{datetime.datetime.now().month}-{datetime.datetime.now().year}.csv'
target_stocks.to_csv(f'file_path/{file_name}')
Answered By - Abhishek Kumar Answer Checked By - Marilyn (PHPFixing Volunteer)
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