标签：25 toy name Batman dropna NaT 数据处理 缺失

pandas 官方 api

1. 函数原型

DataFrame.dropna(axis=0, how='any', thresh=None, subset=None, inplace=False)

2. 参数意义

• axis{0 or ‘index’, 1 or ‘columns’}, default 0

  • Determine if rows or columns which contain missing values are removed.
    • 0, or ‘index’ : Drop rows which contain missing values.
    • 1, or ‘columns’ : Drop columns which contain missing value.
  • Changed in version 1.0.0: Pass tuple or list to drop on multiple axes. Only a single axis is allowed.

• how{‘any’, ‘all’}, default ‘any’

  • Determine if row or column is removed from DataFrame, when we have at least one NA or all NA.
    • ‘any’ : If any NA values are present, drop that row or column.
    • ‘all’ : If all values are NA, drop that row or column.

• threshint, optional

  • Require that many non-NA values.

• subsetarray-like, optional

  • Labels along other axis to consider, e.g. if you are dropping rows these would be a list of columns to include.

• inplacebool, default False

  • If True, do operation inplace and return None.

• Returns

  • DataFrame or None
  • DataFrame with NA entries dropped from it or None if inplace=True.

3. 样例

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

	name        toy       born
0    Alfred        NaN        NaT
1    Batman  Batmobile 1940-04-25
2  Catwoman   Bullwhip        NaT

默认删除

df.dropna()

     name        toy       born
1  Batman  Batmobile 1940-04-25

删除所有存在NAN值的列

df.dropna(axis='columns')

       name
0    Alfred
1    Batman
2  Catwoman

删除所有列都为空的行

df.dropna(how='all')

       name        toy       born
0    Alfred        NaN        NaT
1    Batman  Batmobile 1940-04-25
2  Catwoman   Bullwhip        NaT

删除空值大于2的列

df.dropna(thresh=2)

       name        toy       born
1    Batman  Batmobile 1940-04-25
2  Catwoman   Bullwhip        NaT

删除name,toy列为空的行

df.dropna(subset=['name', 'toy'])

       name        toy       born
1    Batman  Batmobile 1940-04-25
2  Catwoman   Bullwhip        NaT

df.dropna(inplace=True)

     name        toy       born
 1  Batman  Batmobile 1940-04-25

标签：25,toy,name,Batman,dropna,NaT,数据处理,缺失
来源： https://blog.csdn.net/weixin_43745072/article/details/112969660

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