dropna for specific column pandas
df = df[df['EPS'].notna()] #instead of dropping, take another DF with non-na values
dropna for specific column pandas
df = df[df['EPS'].notna()] #instead of dropping, take another DF with non-na values
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.html
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