Single column dataframe containing 1D lists using a numpy 2D array

user_8889727 0
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I want to create a new single column pandas dataframe using a 2D numpy array. Apparently, each row should contain 1D lists. Following is a simplified reproducible example.

import pandas as pd
import numpy as np

arr = np.ones((4,3)) # could be any 2D array

What I want is,

       lists
0  [1, 1, 1]
1  [1, 1, 1]
2  [1, 1, 1]
3  [1, 1, 1]

Now, df = pd.DataFrame(arr, columns=['lists']) gives the error,

ValueError: Shape of passed values is (4, 3), indices imply (4, 1)

And df = pd.DataFrame(list(arr), columns=['lists']) gives the error, 

ValueError: 1 columns passed, passed data had 3 columns

Finally, df = pd.DataFrame(arr.flatten(), columns=['lists']) gives a wrong dataframe with all cells having a scalar 1.

How do I get what I want?

pandas dataframe numpy python
3 Answers
data = {"lists": list(arr)}

df = pd.DataFrame(data, columns=['lists'])

print(df)

Output:

             lists
0  [1.0, 1.0, 1.0]
1  [1.0, 1.0, 1.0]
2  [1.0, 1.0, 1.0]
3  [1.0, 1.0, 1.0]
user_126961630

From each row of the 2d array (i.e. a 1d array), construct a singleton tuple that contains that row, and build the DataFrame from that. We can elegantly do this using a generator expression:

>>> df = pd.DataFrame(((x,) for x in arr), columns=['lists'])
>>> df
             lists
0  [1.0, 1.0, 1.0]
1  [1.0, 1.0, 1.0]
2  [1.0, 1.0, 1.0]
3  [1.0, 1.0, 1.0]

The constructor iterates over the tuple, rather than the underlying array, in order to determine the column values in a given row. There is one such value - the 1d array - so that gets stored for that row in the single available column.

The cell values are indeed Numpy arrays:

>>> df['lists'][0]
array([1., 1., 1.])
user_5236120

Get all rows of the array, create dataframe with them. Transpose then add column name.

import pandas as pd
import numpy as np

# ones array
arr = np.ones((4,3), dtype=int)

# get all rows of the array transpose and add column name
df  = pd.DataFrame([list(arr)]).T
df.columns = ['lists']
df
user_83983630
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