pandas || df.dropna() 缺失值删除

df.dropna()函数用于删除dataframe数据中的缺失数据，即 删除NaN数据.

官方函数说明：

DataFrame.dropna(axis=0, how='any', thresh=None, subset=None, inplace=False)Remove missing values.See the User Guide for more on which values are considered missing, and how to work with missing data.ReturnsDataFrameDataFrame with NA entries dropped from it.

参数说明：

测试：

>>>df = pd.DataFrame({"name": ['Alfred', 'Batman', 'Catwoman'],"toy": [np.nan, 'Batmobile', 'Bullwhip'],"born": [pd.NaT, pd.Timestamp("1940-04-25"),pd.NaT]})

>>>dfname toy born0 Alfred NaN NaT1 Batman Batmobile 1940-04-252 Catwoman Bullwhip NaT

删除至少缺少一个元素的行：

>>>df.dropna()name toy born1 Batman Batmobile 1940-04-25

删除至少缺少一个元素的列：

>>>df.dropna(axis=1)name0 Alfred1 Batman2 Catwoman

删除所有元素丢失的行：

>>>df.dropna(how='all')name toy born0 Alfred NaN NaT1 Batman Batmobile 1940-04-252 Catwoman Bullwhip NaT

只保留至少2个非NA值的行：

>>>df.dropna(thresh=2)name toy born1 Batman Batmobile 1940-04-252 Catwoman Bullwhip NaT

从特定列中查找缺少的值：

>>>df.dropna(subset=['name', 'born'])name toy born1 Batman Batmobile 1940-04-25

修改原数据：

>>>df.dropna(inplace=True)>>>dfname toy born1 Batman Batmobile 1940-04-25

以上。