在 dataframe 中创建一个新列，其中包含列表中该行的其他列的值

Question

I want to change

This datafrme to the

how should I use apply function to achive this?

Answer 1

Try this:

df['bbox'] = df.apply(lambda x: [y for y in x], axis=1)

so for a df that looks like:

In [15]: df
Out[15]:
   a  b  c
0  1  3  1
1  2  4  1
2  3  5  1
3  4  6  1

you'll get:

In [16]: df['bbox'] = df.apply(lambda x: [y for y in x], axis=1)

In [17]: df
Out[17]:
   a  b  c       bbox
0  1  3  1  [1, 3, 1]
1  2  4  1  [2, 4, 1]
2  3  5  1  [3, 5, 1]
3  4  6  1  [4, 6, 1]

Hope this helps!

Answer 2

As per your example to achieve required result, you need to convert each row in list. Add that list to new DataFrame. Once you add new list to DataFrame apply whatever calculation(your output DataFrame values are different from input DataFrame hence expecting you have done some calculation on each cell or row) you want to apply on the same.

import pandas as pd
data = {'x':[121,216,49],'y':[204,288,449],'w':[108,127,184]}
df = pd.DataFrame(data,columns=['x','y','w'])
new_data = [[row.to_list()] for i, row in df.iterrows()]
new_df = pd.DataFrame(new_data, columns='bbox')
print(new_df)

            bbox
0 [121, 216, 49]
1 [204, 288,449]
2 [108, 127, 184]