So I have a pandas data frame similar to this:

and I want to unpack it so that it becomes 5 columns as apparently tensorflow doesn't support nested lists. Is there an efficient way to achieve this?

CodePudding user response：

You can try merging the lists with pandas:

import pandas as pd

df = pd.DataFrame(data = {'col1': [[0,1,0], [1,0,0] ], 'col2': [1, 0], 'col3': [0, 1]})

df['col1-1'], df['col1-2'], df['col1-3'] = zip(*list(df['col1'].values))
df = df.drop('col1', axis=1)
print(df)

   col2  col3  col1-1  col1-2  col1-3
0     1     0       0       1       0
1     0     1       1       0       0

Or with numpy:

import pandas as pd
import numpy as np

df = pd.DataFrame(data = {'col1': [[0,1,0], [1,0,0] ], 'col2': [1, 0], 'col3': [0, 1]})

col1 = np.vstack(df['col1'].values)
col23 = df[['col2', 'col3']].values

data = np.concatenate([col1, col23], axis=-1)
print(data)

[[0 1 0 1 0]
 [1 0 0 0 1]]