DataFrame.dropna(axis=0, how='any', thresh=None, subset=None, inplace=False)
df.dropna(axis=0/'index') # Drop rows which contain missing values.
df.dropna(axis=1/'column') # Drop columns which contain missing values.
df.dropna(how='any')
df.dropna(how='all')
df.dropna(thresh=2) # int
df.dropna(axis=0, subset=['column1', 'column2', ..., 'columnp'])
df.dropna(axis=1, subset=['index1', 'index2', ..., 'indexq'])
df.dropna(inplace=True)
DataFrame.drop_duplicates(subset=None, keep='first', inplace=False)
df.drop_duplicates()
df.drop_duplicates(subset='column1')
df.drop_duplicates(subset=['column1', 'column2', ..., 'columnp'])
df.drop_duplicates(keep='first')
df.drop_duplicates(keep='last')
df.drop_duplicates(keep=False)
df.drop_duplicates(inplace=True)