如何将 pandas 数据帧加载并保存到 excel.csv 文件

Question

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.

Answer 1

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}')

Answer 2

If you want the code to have the day in which you run the code you can use:

import os
import datetime

target_stocks.to_csv(os.path.join("desired_path",str(datetime.datetime.now().date()))