Question

列出了加载到pandas dataframe df2中的人员的属性。对于清理，我想将值0或'0'替换为np.nan。

df2.dtypes

ID                   object
Name                 object
Weight              float64
Height              float64
BootSize             object
SuitSize             object
Type                 object
dtype: object

使用代码将值0设置为np.nan：

df2.loc[df2['Weight'] == 0,'Weight'] = np.nan
df2.loc[df2['Height'] == 0,'Height'] = np.nan
df2.loc[df2['BootSize'] == '0','BootSize'] = np.nan
df2.loc[df2['SuitSize'] == '0','SuitSize'] = np.nan

相信这可以用类似/更短的方式完成：

df2[["Weight","Height","BootSize","SuitSize"]].astype(str).replace('0',np.nan)

但是上述方法不起作用。零保留在df2中。如何解决这个问题？

Answer 1

我认为dict需要replace：

cols = ["Weight","Height","BootSize","SuitSize","Type"]
df2[cols] = df2[cols].replace({'0':np.nan, 0:np.nan})

Answer 2

您可以使用'replace'方法并将要替换的值作为第一个参数传递给列表，并将所需的值作为第二个参数传递给

cols = ["Weight","Height","BootSize","SuitSize","Type"]
df2[cols] = df2[cols].replace(['0', 0], np.nan)

Answer 3

data['amount']=data['amount'].replace(0, np.nan)
data['duration']=data['duration'].replace(0, np.nan)

Answer 4

尝试：

df2.replace(to_replace={
             'Weight':{0:np.nan}, 
             'Height':{0:np.nan},
             'BootSize':{'0':np.nan},
             'SuitSize':{'0':np.nan},
                 })

Answer 5

另一种方法：

cols = ["Weight","Height","BootSize","SuitSize","Type"]
df2[cols] = df2[cols].mask(df2[cols].eq(0) | df2[cols].eq('0'))

Answer 6

在“年龄”列中，用空格替换零

@Bean
public MessageConverter jacksonJmsMessageConverter() {
    MappingJackson2MessageConverter converter = new MappingJackson2MessageConverter();
    converter.setTargetType(MessageType.TEXT);
    converter.setTypeIdPropertyName("_type");
    return converter;
}

单列用nan替换零

    public function renderAddForm()
    {
        $fields_form[0]['form'] = array(
            'legend' => array(
                'title' => $this->l('Impostazione App Mobile'),
            ),
            'input' => array(
                array(
                    'type' => 'categories',
                    'label' => $this->l('Seleziona Categoria'),
                    'name' => 'name',
                    'tree'  => array(
                        'id' => 'category',
                        'name' => 'name',
                        'selected_categories' => array((int)Configuration::get('category')),
                        'use_checkbox' => false
                    )
                ),

多列用 nan 替换零

df['age'].replace(['0', 0'], '', inplace=True)

用 nan 替换数据框的零

df['age'] = df['age'].replace(0, np.nan)

Python Pandas将多个列替换为零到Nan

6 个答案: