I'm trying to replace all NaN values in a dataframe with an array [NaN, NaN, NaN] instead. But the normal replace methods (df.replace) don't work because to_replace and value are not the same size.
Thanks in advance :)
2 Answers
Recomend you Read: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.dropna.html
Also you Must See this: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.fillna.html#pandas.DataFrame.fillna
If this Help let me Know Please, I'm New on Stackoverflow and i'll try to Help When i See Something that i Can Help. Thanks.
1 Comment
Pixie Nielsen
It was very helpful! Dived into df.fillna and solved the problem. Thanks
I figured something, that should work:
import pandas as pd
import numpy as np
# Sample df with a NaN in column "y"
df = pd.DataFrame({"y": np.NaN, "x": ["Some Value"]})
# Get the nans
isna = df['y'].isna()
# Replace with series with list of (3) nans
df.loc[isna, 'y'] = pd.Series([[np.NaN, np.NaN, np.NaN]] * isna.sum()).values
print(df)
Mainly taken from: https://stackoverflow.com/a/61944174/5635941
