soltar se nan em pandas colunas
df = df[df['EPS'].notna()]
Hambo
df = df[df['EPS'].notna()]#return a subset of the dataframe where the column name value != NaN
df.loc[df['column name'].isnull() == False] df = df[df['my_var'].notna()]In [30]: df.dropna(subset=[1]) #Drop only if NaN in specific column (as asked in the question)
Out[30]:
0 1 2
1 2.677677 -1.466923 -0.750366
2 NaN 0.798002 -0.906038
3 0.672201 0.964789 NaN
5 -1.250970 0.030561 -2.678622
6 NaN 1.036043 NaN
7 0.049896 -0.308003 0.823295
9 -0.310130 0.078891 NaN
a = [[y for y in x if pd.notna(y)] for x in df.values.tolist()]
print (a)
[['str', 'aad', 'asd'], ['ddd'], ['xyz', 'abc'], ['btc', 'trz', 'abd']]