python dropna 的用法

Posted 2020-10-30 YingxuanZHANG

"""
Return object with labels on given axis omitted where alternately any
or all of the data are missing

Parameters
----------
axis : {0 or ‘index‘, 1 or ‘columns‘}, or tuple/list thereof
Pass tuple or list to drop on multiple axes
how : {‘any‘, ‘all‘}
* any : if any NA values are present, drop that label
* all : if all values are NA, drop that label
thresh : int, default None
int value : require that many non-NA values
subset : array-like
Labels along other axis to consider, e.g. if you are dropping rows
these would be a list of columns to include
inplace : boolean, default False
If True, do operation inplace and return None.

Returns
-------
dropped : DataFrame

Examples
--------
>>> df = pd.DataFrame([[np.nan, 2, np.nan, 0], [3, 4, np.nan, 1],
... [np.nan, np.nan, np.nan, 5]],
... columns=list(‘ABCD‘))
>>> df
A B C D
0 NaN 2.0 NaN 0
1 3.0 4.0 NaN 1
2 NaN NaN NaN 5

Drop the columns where all elements are nan:

>>> df.dropna(axis=1, how=‘all‘)
A B D
0 NaN 2.0 0
1 3.0 4.0 1
2 NaN NaN 5

Drop the columns where any of the elements is nan

>>> df.dropna(axis=1, how=‘any‘)
D
0 0
1 1
2 5

Drop the rows where all of the elements are nan
(there is no row to drop, so df stays the same):

>>> df.dropna(axis=0, how=‘all‘)
A B C D
0 NaN 2.0 NaN 0
1 3.0 4.0 NaN 1
2 NaN NaN NaN 5

Keep only the rows with at least 2 non-na values:

>>> df.dropna(thresh=2)
A B C D
0 NaN 2.0 NaN 0
1 3.0 4.0 NaN 1

"""