shazování nan v pandy dataframe
df.dropna(subset=['name', 'born'])
pandy 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
dropna pandy
>>> df.dropna(axis='columns')
name
0 Alfred
1 Batman
2 Catwoman
prahová hodnota dropna
#dropping columns having more than 50% missing values(1994/2==1000)
df=df.dropna(thresh=1000,axis=1)