How to remove rows in a dataframe with more than x number of Null values? [duplicate]

Question

I am trying to remove the rows in the data frame with more than 7 null values. Please suggest something that is efficient to achieve this.

Answer 1

If I understand correctly, you need to remove rows only if total nan's in a row is more than 7:

df = df[df.isnull().sum(axis=1) < 7]

This will keep only rows which have nan's less than 7 in the dataframe, and will remove all having nan's > 7.

Answer 2

dropna has a thresh argument. Subtract your desired number from the number of columns.

thresh : int, optional Require that many non-NA values.

df.dropna(thresh=df.shape[1]-7, axis=0)

Sample Data:

print(df)
     0    1     2     3     4     5     6     7
0  NaN  NaN   NaN   NaN   NaN   NaN   NaN   NaN
1  NaN  NaN   NaN   NaN   NaN   NaN   NaN   5.0
2  6.0  7.0   8.0   9.0   NaN   NaN   NaN   NaN
3  NaN  NaN  11.0  12.0  13.0  14.0  15.0  16.0

df.dropna(thresh=df.shape[1]-7, axis=0)
     0    1     2     3     4     5     6     7
1  NaN  NaN   NaN   NaN   NaN   NaN   NaN   5.0
2  6.0  7.0   8.0   9.0   NaN   NaN   NaN   NaN
3  NaN  NaN  11.0  12.0  13.0  14.0  15.0  16.0