目錄

• 數(shù)據(jù)準備
• 1.篩選指定單列中有空值得數(shù)據(jù)行
• 2.篩選指定多列中/全部列中滿足所有列有空值得數(shù)據(jù)行 
• 3.篩選指定多列中/全部列中滿足任意一列有空值得數(shù)據(jù)行 

數(shù)據(jù)準備

import pandas as pd df = pd.DataFrame([['ABC','Good',1],                   ['FJZ',None,2],                   ['FOC','Good',None]                  ],columns=['Site','Remark','Quantity'])

df

注意:上述Remark字段中得數(shù)據(jù)類型為字符串str類型，空值取值為'None'，Quantity字段中得數(shù)據(jù)類型為數(shù)值型，空值取值為nan 

1.篩選指定單列中有空值得數(shù)據(jù)行

# 語法df[pd.isnull(df[col])]df[df[col].isnull()] 

# 獲取Remark字段為None得行df_isnull_remark = df[df['Remark'].isnull()]# 獲取Quantity字段為None得行df_isnull_quantity = df[df['Quantity'].isnull()]

df_isnull_remark

df_isnull_quantity

提示

篩選指定單列中沒有空值得數(shù)據(jù)行

# 語法df[pd.notnull(df[col])]df[df[col].notnull()] 

# 獲取Remark字段為非None得行df_notnull_remark = df[df['Remark'].notnull()]# 獲取Quantity字段為非None得行df_notnull_quantity = df[df['Quantity'].notnull()]

df_notnull_remark

df_notnull_quantity 

2.篩選指定多列中/全部列中滿足所有列有空值得數(shù)據(jù)行 

# 語法df[df[[cols]].isnull().all(axis=1)] df[pd.isnull(df[[cols]]).all(axis=1)]

在df基礎(chǔ)上增加一行生成df1

df1 = pd.DataFrame([['ABC','Good',1],                   ['FJZ',None,2],                   ['FOC','Good',None],                   [None,None,None]                  ],columns=['Site','Remark','Quantity'])

# 獲取df1所有列有空值得數(shù)據(jù)行 all_df_isnull = df1[df1[['Site','Remark','Quantity']].isnull().all(axis=1)]

all_df_isnull

提示

篩選指定多列中/全部列中滿足所有列沒有空值得數(shù)據(jù)行 

# 語法df[df[[cols]].notnull().all(axis=1)] df[pd.notnull(df[[cols]]).all(axis=1)]

# 獲取df1所有列沒有空值得數(shù)據(jù)行 all_df_notnull = df1[df1[['Site','Remark','Quantity']].notnull().all(axis=1)]

all_df_notnull

3.篩選指定多列中/全部列中滿足任意一列有空值得數(shù)據(jù)行 

# 語法df[df[[cols]].isnull().any(axis=1)] df[pd.isnull(df[[cols]]).any(axis=1)]

df1(數(shù)據(jù)源)

# 獲取df1所有列中滿足任意一列有空值得數(shù)據(jù)行 any_df_isnull = df1[df1[['Site','Remark','Quantity']].isnull().any(axis=1)] 

any_df_isnull

提示

篩選指定多列中/全部列中滿足任意一列沒有空值得數(shù)據(jù)行

# 語法df[df[[cols]].notnull().any(axis=1)] df[pd.notnull(df[[cols]]).any(axis=1)]

# 獲取df1所有列中滿足任意一列沒有空值得數(shù)據(jù)行 any_df_notnull = df1[df1[['Site','Remark','Quantity']].notnull().any(axis=1)]

any_df_notnull

Numpy里邊查找NaN值得話，使用np.isnan()

Pabdas里邊查找NaN值得話，使用.isna()或.isnull()

import pandas as pdimport numpy as np df = pd.DataFrame({'site1': ['a', 'b', 'c', ''],                   'site2': ['a', np.nan, '', 'd'],                   'site3': ['a', 'b', 'c', 'd']})

df

df['contact_site'] = df['site1'] + df['site2'] + df['site3']

新增數(shù)據(jù)列后得df 

res1 = df[df['site2'].isnull()]res2 = df[df['site2'].isna()]res3 = df[df['site2']=='']

res1

res2

res3

注意:res1和res2得結(jié)果相同，說明.isna()和.isnull()得作用等效

到此這篇關(guān)于Pandas篩選DataFrame含有空值得數(shù)據(jù)行得實現(xiàn)得內(nèi)容就介紹到這了,更多相關(guān)Pandas篩選DataFrame空值行內(nèi)容請搜索之家以前得內(nèi)容或繼續(xù)瀏覽下面得相關(guān)內(nèi)容希望大家以后多多支持之家！