Sort rows of a dataframe in descending order of NaN counts

Question

I\'m trying to sort the following Pandas DataFrame:

         RHS  age  height  shoe_size  weight
0     weight  NaN     0.0        0.0     1.0
1  shoe_size  N         


        

Answer 1

Using df.sort_values and loc based accessing.

df = df.iloc[df.isnull().sum(1).sort_values(ascending=0).index]
print(df)

         RHS  age  height  shoe_size  weight
1  shoe_size  NaN     0.0        1.0     NaN
2  shoe_size  3.0     0.0        0.0     NaN
0     weight  NaN     0.0        0.0     1.0
4        age  3.0     0.0        0.0     1.0
3     weight  3.0     0.0        0.0     1.0

df.isnull().sum(1) counts the NaNs and the rows are accessed based on this sorted count.

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@ayhan offered a nice little improvement to the solution above, involving pd.Series.argsort:

df = df.iloc[df.isnull().sum(axis=1).mul(-1).argsort()]
print(df)

         RHS  age  height  shoe_size  weight 
1  shoe_size  NaN     0.0        1.0     NaN           
0     weight  NaN     0.0        0.0     1.0           
2  shoe_size  3.0     0.0        0.0     NaN           
3     weight  3.0     0.0        0.0     1.0           
4        age  3.0     0.0        0.0     1.0