remove nan from a column pandas code example
Example 1: how to delete na values in a dataframe
# if you want to delete rows containing NA values
df.dropna(inplace=True)
Example 2: pandas dropna
df = pd.DataFrame({"name": ['Alfred', 'Batman', 'Catwoman'],
... "toy": [np.nan, 'Batmobile', 'Bullwhip'],
... "born": [pd.NaT, pd.Timestamp("1940-04-25"),
... pd.NaT]})
>>> df
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()
name toy born
1 Batman Batmobile 1940-04-25
Example 3: Returns a new DataFrame omitting rows with null values
# Returns a new DataFrame omitting rows with null values
df4.na.drop().show()
# +---+------+-----+
# |age|height| name|
# +---+------+-----+
# | 10| 80|Alice|
# +---+------+-----+
Example 4: when 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']]