Duplicate DataFrame with new columns with different values

Question

I have a pandas DataFrame.

import pandas as pd
import numpy as np
from datetime import datetime

d = {'account_id': [1, 2], 'type': ['a', 'b']}
df = pd.DataFrame(data=d)

	account_id	type
0	1	a
1	2	b

I want to add two columns include_images and data_since which should contain one time True and a date for every row of the original DataFrame and one time False and NaN for every row of the original DataFrame.

Is there a more efficient way of writing this then like so:

df_a = df.copy()
df_a['include_images'] = True
df_a['data_since'] = datetime(2018, 1, 1)

df_b = df.copy()
df_b['include_images'] = False
df_b['data_since'] = np.nan

df = pd.concat([df_a, df_b], ignore_index=True)

	account_id	type	include_images	data_since
0	1	a	True	2018-01-01 00:00:00
1	2	b	True	2018-01-01 00:00:00
2	1	a	False	NaT
3	2	b	False	NaT

what do you mean by more efficient here? is it to have a more parametric way to do it because your end goal is to duplicates df many times with a lot of different values in the two extra columns? — Ben.T
– Ben.T, Commented May 31, 2021 at 14:17

Quang Hoang · Accepted Answer · 2021-05-31 14:24:59Z

2

Try assign which creates a copy on-the-fly:

const_date = pd.Timestamp('2018-01-01')

out = pd.concat([df.assign(include_img=True, data_since=const_date),
                 df.assign(include_img=False, data_since=pd.NaT)],
                ignore_index=True)

Output:

   account_id type  include_img data_since
0           1    a         True 2018-01-01
1           2    b         True 2018-01-01
2           1    a        False        NaT
3           2    b        False        NaT

answered May 31, 2021 at 14:24

Quang Hoang

151k11 gold badges64 silver badges86 bronze badges

Sign up to request clarification or add additional context in comments.

Comments

Riccardo Bucco · Accepted Answer · 2021-05-31 14:12:37Z

0

Here is a possible solution:

df = pd.concat([df, df], ignore_index=True)
df['include_images'] = False
df['data_since'] = np.nan
df.loc[range(len(df) // 2), ('include_images', 'data_since')] = (True, datetime(2018, 1, 1))

answered May 31, 2021 at 14:12

Riccardo Bucco

15.5k4 gold badges29 silver badges57 bronze badges

Collectives™ on Stack Overflow

Duplicate DataFrame with new columns with different values

2 Answers 2

Comments

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

2 Answers 2

Comments

Comments

Your Answer

Sign up or log in

Post as a guest

Related