Getting the NaN rows from pandas.dropna

Question

I am using dropna to get rid of the NaN values, but instead of just dropping them i want to get a new table where those rows are saved. That's to say from the current code:

df_weight.dropna(subset = ["age"], inplace=True)
df_weight.dropna(subset = ["height"], inplace=True)
df_weight.dropna(subset = ["weight"], inplace=True)
df_weight

i want to save the rows that are droppen in the line df_weight.dropna(subset = ["weight"], inplace=True) . I think that dropna does not have a return value, so there is any work around to archive this?

EDIT: my db comes from https://data.world/bgadoci/crossfit-data/workspace/file?filename=athletes.csv . I deleted all the other rows to make a mini db: after loading the data into pandas i do df_weight = df[['gender','age','height','weight']] with the code mentioned above i get something like this (where the desired row datatype is marked)

Answer 1

you can try as follows. if you share the DF, it will be easier to reproduce and provide the working solution

its an idea or direction

df_weight.isna()['age']
df_weight.isna()['height']
df_weight.isna()['weight']

Answer 2

You could use

dropped_rows_df =  df_weight[df_weight[['age','height','weight']]].isna().any(axis=1)]

#then
df_weight.dropna(subset = ["age"], inplace=True)
df_weight.dropna(subset = ["height"], inplace=True)
df_weight.dropna(subset = ["weight"], inplace=True)
df_weight