How to drop rows in python based on null values

Question

Hello: I have the following code that gives me a count of the number of null values in a column:

df_null = df.columns[df.isnull().any()]

df[df_null].isnull().sum()

The result is an index with the column name and number of null values:

col1 10  
col2 20  
col3 30  

What I want to do is drop all the rows/records in columns that have less than 15 null values. I have gone through the columns manually and dropped the rows/records using the following:

df.dropna(subset=['col_name'], axis=0, inplace=True)

That works fine. But what I would like to do is automate the process so I don't have to manually go through each column and drop the null rows/records manually.

Thank you.

Answer 1

Check with

s = df.isnull().sum()
dfnew = df.loc[:, (s>15)|(s==0)]
# the first condition will keep column with more than 15 null, then second , will keep all column without have NaN

Answer 2

Another way

Keep only the columns with at least n non-NaN values

n=len(df)-15


 df.dropna(thresh=n, axis=1)