drop if nan in column pandas
df = df[df['EPS'].notna()]remove nan from list python
cleanedList = [x for x in countries if str(x) != 'nan']how to filter out all NaN values in pandas df
#return a subset of the dataframe where the column name value != NaN
df.loc[df['column name'].isnull() == False]dropna pandas
df = pd.DataFrame({"name": ['Alfred', 'Batman', 'Catwoman'],
"toy": [np.nan, 'Batmobile', 'Bullwhip'],
"born": [pd.NaT, pd.Timestamp("1940-04-25"),
pd.NaT]})
df
# o/p
# name toy born
# 0 Alfred NaN NaT
# 1 Batman Batmobile 1940-04-25
# 2 Catwoman Bullwhip NaT
# Drop the rows where at least one element is missing.
df.dropna()
# o/p
# name toy born
# 1 Batman Batmobile 1940-04-25
# ref. https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.dropna.htmlwhen converting from dataframe to list delete nan values
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']]Copyright © 2021 Codeinu
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