How to filter in NaN (pandas)?
Question:
I have a pandas dataframe (df), and I want to do something like:
newdf = df[(df.var1 == 'a') & (df.var2 == NaN)]
I’ve tried replacing NaN with np.NaN, or 'NaN' or 'nan' etc, but nothing evaluates to True. There’s no pd.NaN.
I can use df.fillna(np.nan) before evaluating the above expression but that feels hackish and I wonder if it will interfere with other pandas operations that rely on being able to identify pandas-format NaN’s later.
I get the feeling there should be an easy answer to this question, but somehow it has eluded me. Any advice is appreciated. Thank you.
Answers:
This doesn’t work because NaN isn’t equal to anything, including NaN. Use pd.isnull(df.var2) instead.
Pandas uses numpy‘s NaN value. Use numpy.isnan to obtain a Boolean vector from a pandas series.
Simplest of all solutions:
filtered_df = df[df['var2'].isnull()]
This filters and gives you rows which has only NaN values in 'var2' column.
df[df['var'].isna()]
where
df : The DataFrame
var : The Column Name
I have a pandas dataframe (df), and I want to do something like:
newdf = df[(df.var1 == 'a') & (df.var2 == NaN)]
I’ve tried replacing NaN with np.NaN, or 'NaN' or 'nan' etc, but nothing evaluates to True. There’s no pd.NaN.
I can use df.fillna(np.nan) before evaluating the above expression but that feels hackish and I wonder if it will interfere with other pandas operations that rely on being able to identify pandas-format NaN’s later.
I get the feeling there should be an easy answer to this question, but somehow it has eluded me. Any advice is appreciated. Thank you.
This doesn’t work because NaN isn’t equal to anything, including NaN. Use pd.isnull(df.var2) instead.
Pandas uses numpy‘s NaN value. Use numpy.isnan to obtain a Boolean vector from a pandas series.
Simplest of all solutions:
filtered_df = df[df['var2'].isnull()]
This filters and gives you rows which has only NaN values in 'var2' column.
df[df['var'].isna()]
where
df : The DataFrame
var : The Column Name