How do I implement separator in a dataset loaded directly from sklearn library?

Question

I know how to use separator (sep ="") when importing the dataset using pd.read_csv

but I don’t know what to use to implement the separator on a dataset loaded from sklearn itself, like the digits dataset i used below where i want to implement the n separator.

code:

from sklearn.datasets import load_digits
import pandas as pd
df = load_digits()
print(df)

Asked By: Marka Ragnos

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Source

Answer 1

If you look at carefully, you’ll see that load_digits is a dictionary. You can reach its elements by

df.keys()

which returns

dict_keys(['data', 'target', 'frame', 'feature_names', 'target_names', 'images', 'DESCR'])

So, if you want to get the data, just call the data key

df['data']

returns

[[ 0.  0.  5. ...  0.  0.  0.]
[ 0.  0.  0. ... 10.  0.  0.]
 [ 0.  0.  0. ... 16.  9.  0.]
 ...
 [ 0.  0.  1. ...  6.  0.  0.]
 [ 0.  0.  2. ... 12.  0.  0.]
 [ 0.  0. 10. ... 12.  1.  0.]]

Answered By: Nuri Taş

How do I implement separator in a dataset loaded directly from sklearn library?

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