I have a dataframe df with a single column that contains arrays of length 3. Now, I want to transform this column to a numpy array of the correct shape. However, applying np.reshape does not work. How can I do this?
Here is a brief example:
import pandas as pd
import numpy as np
df = pd.DataFrame(columns=['col'])
for i in range(10):
df.loc[i,'col'] = np.zeros(3)
arr = np.array(df['col'])
np.reshape(arr, (10,3)) # This does not work
Here are two approaches using np.vstack and np.concatenate -
np.vstack(df.col)
np.concatenate(df.col).reshape(df.shape[0],-1) # for performance
For best performance, we could use the underlying data with df.col.values instead.
Sample run -
In [116]: df
Out[116]:
col
0 [7, 5, 2]
1 [1, 1, 3]
2 [6, 1, 4]
3 [7, 0, 0]
4 [8, 8, 0]
5 [7, 8, 0]
6 [0, 5, 8]
7 [8, 3, 1]
8 [6, 6, 8]
9 [8, 2, 3]
In [117]: np.vstack(df.col)
Out[117]:
array([[7, 5, 2],
[1, 1, 3],
[6, 1, 4],
[7, 0, 0],
[8, 8, 0],
[7, 8, 0],
[0, 5, 8],
[8, 3, 1],
[6, 6, 8],
[8, 2, 3]])
