Creating new dataframe from preexisting dataframe using Python

Question

I have a large file, df1, that I wish to extract some data from its cells and then create a new file, df2 with a new column name and datetime column:

df

        A   B   C   D   E
        
        1   2   3   4   5

Desired output:

    Date       Value

    1/1/2020   3

This is what I am doing:

   import pandas as pd
   import numpy as mp

   df1 = pd.read_csv('df1'csv')


   for index.row in df.iterrows():
       print row.loc[0:3] = df2['value']





   df2.to_csv('df2.csv')

I am stuck on how to create the new column and add the date into this new dataframe. Any suggestion is appreciated.

Mayank Porwal · Accepted Answer · 2020-10-20 19:19:06Z

1

Assuming Date is a constant value you need to add, you can do this:

In [1393]: df
Out[1393]: 
   A  B  C  D  E
0  1  2  3  4  5

In [1395]: x = df.at[0, 'C'] # Pick 1st row's column C

In [1396]: y = '1/1/2020'

In [1398]: df = pd.DataFrame({'Date':[y], 'Value':[x]})

In [1399]: df
Out[1399]: 
       Date  Value
0  1/1/2020      3

You can then write this df to an excel file like below:

df.to_excel('file.xlsx')

answered Oct 20, 2020 at 19:19

Mayank Porwal

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3 Comments

Lynn Over a year ago

Thank you I will try. Is there a way to loop through this (if I have multiple values?) for i in df: print...

Mayank Porwal Over a year ago

You can loop through the dataframe using df,iterrows(). Something like: for I in df.iterrows()`. You can easily find multiple answers related to it.

Lynn Over a year ago

I will try this process - this is helpful

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