pandas.DataFrame.isna |
您所在的位置：网站首页 › isnas › pandas.DataFrame.isna |
|
Detect missing values. Return a boolean same-sized object indicating if the values are NA. NA values, such as None or numpy.NaN, gets mapped to True values. Everything else gets mapped to False values. Characters such as empty strings '' or numpy.inf are not considered NA values (unless you set pandas.options.mode.use_inf_as_na = True). Returns DataFrameMask of bool values for each element in DataFrame that indicates whether an element is an NA value. See also DataFrame.isnullAlias of isna. DataFrame.notnaBoolean inverse of isna. DataFrame.dropnaOmit axes labels with missing values. isnaTop-level isna. Examples Show which entries in a DataFrame are NA. >>> df = pd.DataFrame(dict(age=[5, 6, np.NaN], ... born=[pd.NaT, pd.Timestamp('1939-05-27'), ... pd.Timestamp('1940-04-25')], ... name=['Alfred', 'Batman', ''], ... toy=[None, 'Batmobile', 'Joker'])) >>> df age born name toy 0 5.0 NaT Alfred None 1 6.0 1939-05-27 Batman Batmobile 2 NaN 1940-04-25 Joker >>> df.isna() age born name toy 0 False True False True 1 False False False False 2 True False False FalseShow which entries in a Series are NA. >>> ser = pd.Series([5, 6, np.NaN]) >>> ser 0 5.0 1 6.0 2 NaN dtype: float64 >>> ser.isna() 0 False 1 False 2 True dtype: bool |
| CopyRight 2018-2019 办公设备维修网 版权所有 豫ICP备15022753号-3 |