Why do i get all date similiar while trying to fill them in dataset?-CodePudding

I have dataset with 800 rows and i want to create new column with date, and in each row in should increase on one day.

import datetime
date = datetime.datetime.strptime('5/11/2011', '%d/%m/%Y')
for x in range(800):
    df['Date'] = date   datetime.timedelta(days=x)

In each column date is equal to '2014-01-12', as i inderstand it fills as if x is always equal to 799

CodePudding user response：

Each time through the loop you are updating the ENTIRE Date column. You see the results of the 800th update at the end.

You could use a date range:

dr = pd.date_range('5/11/2011', periods=800, freq='D')

df = pd.DataFrame({'Date': dr})
print(df)

          Date
0   2011-05-11
1   2011-05-12
2   2011-05-13
3   2011-05-14
4   2011-05-15
..         ...
795 2013-07-14
796 2013-07-15
797 2013-07-16
798 2013-07-17
799 2013-07-18

Or:

df['Date'] = dr

CodePudding user response：

pandas is nice tool which can repeate some calculations without using for-loop.

When you use df['Date'] = ... then you assign the same value to all cells in column.

You have to use df.loc[x, 'Date'] = ... to assign to single cell.

Minimal working example (with only 10 rows).

import pandas as pd
import datetime

df = pd.DataFrame({'Date':[1,2,3,4,5,6,7,8,9,0]})

date = datetime.datetime.strptime('5/11/2011', '%d/%m/%Y')

for x in range(10):
    df.loc[x,'Date'] = date   datetime.timedelta(days=x)
    
print(df)

But you could use also pd.date_range() for this.

Minimal working example (with only 10 rows).

import pandas as pd
import datetime

df = pd.DataFrame({'Date':[1,2,3,4,5,6,7,8,9,0]})

date = datetime.datetime.strptime('5/11/2011', '%d/%m/%Y')

df['Date'] = pd.date_range(date, periods=10)
    
print(df)