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| 172 | [ NumPy 的pad填充方法] ( md/172.md ) | NumPy pad | V1.0 | ⭐️⭐⭐⭐ |
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| 173 | [ 创建下对角线为1、2、3、4的对角矩阵] ( md/173.md ) | NumPy diag | V1.0 | ⭐️⭐⭐ |
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| 174 | [ cut 数据分箱] ( md/174.md ) | Pandas cut | v1.0 | ⭐️⭐⭐ |
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+ | | [ 丢弃空值和填充空值] ( ./md/175.md ) | Pandas dropna fillna | v1.0 | ⭐️⭐⭐ |
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### Python 实战
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``` markdown
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@author jackzhenguo
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- @desc
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+ @desc 丢弃空值和填充空值
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@tag
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@version
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@date 2020/03/13
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```
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+ 丢弃空值
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+ np.nan 是 pandas 中常见空值,使用 dropna 过滤空值,axis 0 表示按照行,1 表示按列,how 默认为 any ,意思是只要有一个 nan 就过滤某行或某列,all 所有都为 nan
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+
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+ ``` python
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+ # axis 0 表示按照行,all 此行所有值都为 nan
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+ df.dropna(axis = 0 , how = ' all' )
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+ ```
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+
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+ 充填空值
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+ 空值一般使用某个统计值填充,如平均数、众数、中位数等,使用函数 fillna:
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+ ``` python
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+ # 使用a列平均数填充列的空值,inplace true表示就地填充
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+ df[" a" ].fillna(df[" a" ].mean(), inplace = True )
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+ ```
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+
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