如何从一个 zip 在 dataframe 中创建 2 列

Question

I wish to turn the zips in the 3rd columns into 2 different columns with either number as seen in df2, how would I do this?

import pandas as pd
import numpy as np
data = pd.DataFrame(([[1, 2, (3,5)], [4, 5, (6,4)], [7, 8, (9,1)]]), columns = ['a', 'b', 'c and d'])
print (data)

the desired output:

data2 = pd.DataFrame(([[1, 2, 3,5], [4, 5, 6,4], [7, 8, 9,1]]), columns = ['a', 'b', 'c', 'd'])
print(data2)

Answer 1

You can pop the column so it's removed and then use the DataFrame constructor on the list of tuples. Join the results.

res = pd.concat([data, pd.DataFrame(data.pop('c and d').tolist(), columns=['c', 'd'])], axis=1)

   a  b  c  d
0  1  2  3  5
1  4  5  6  4
2  7  8  9  1

---

More straight-forward, you can assign the elements of the tuples with the Series.str accessor, then delete the column.

data['c'] = data['c and d'].str[0]
data['d'] = data['c and d'].str[1]
data = data.drop(columns='c and d')

Answer 2

Another solution:

data[["c", "d"]] = data["c and d"].apply(pd.Series)
data = data.drop(columns="c and d")
print(data)

Prints:

   a  b  c  d
0  1  2  3  5
1  4  5  6  4
2  7  8  9  1