根据条件在Pandas DataFrame中选择行

时间：2020-10-26 11:54:35 阅读：30 评论：0 收藏：0 [点我收藏+]

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让我们看看如何根据Pandas DataFrame中的某些条件选择行。

使用`‘>‘, ‘=‘, ‘=‘, ‘<=‘, ‘!=‘` 运算符根据特定的列值选择行。

代码1：使用基本方法从给定数据框中选择‘Percentage‘大于80的所有行。

# importing pandas 
import pandas as pd 

record = { 

‘Name‘: [‘Ankit‘, ‘Amit‘, ‘Aishwarya‘, ‘Priyanka‘, ‘Priya‘, ‘Shaurya‘ ], 
‘Age‘: [21, 19, 20, 18, 17, 21], 
‘Stream‘: [‘Math‘, ‘Commerce‘, ‘Science‘, ‘Math‘, ‘Math‘, ‘Science‘], 
‘Percentage‘: [88, 92, 95, 70, 65, 78] } 

# create a dataframe 
dataframe = pd.DataFrame(record, columns = [‘Name‘, ‘Age‘, ‘Stream‘, ‘Percentage‘]) 

print("Given Dataframe :\n", dataframe) 

# selecting rows based on condition 
rslt_df = dataframe[dataframe[‘Percentage‘] > 80] 

print(‘\nResult dataframe :\n‘, rslt_df)

技术图片

代码2：使用选择从给定数据帧中‘Percentage‘大于80的所有行loc[]。

# importing pandas 
import pandas as pd 

record = { 
‘Name‘: [‘Ankit‘, ‘Amit‘, ‘Aishwarya‘, ‘Priyanka‘, ‘Priya‘, ‘Shaurya‘ ], 
‘Age‘: [21, 19, 20, 18, 17, 21], 
‘Stream‘: [‘Math‘, ‘Commerce‘, ‘Science‘, ‘Math‘, ‘Math‘, ‘Science‘], 
‘Percentage‘: [88, 92, 95, 70, 65, 78]} 

# create a dataframe 
dataframe = pd.DataFrame(record, columns = [‘Name‘, ‘Age‘, ‘Stream‘, ‘Percentage‘]) 

print("Given Dataframe :\n", dataframe) 

# selecting rows based on condition 
rslt_df = dataframe.loc[dataframe[‘Percentage‘] > 80] 

print(‘\nResult dataframe :\n‘, rslt_df)

输出：

技术图片

代码＃3：使用选择从给定数据帧中‘Percentage‘不等于95的所有行loc[]。

# importing pandas 
import pandas as pd 

record = { 
‘Name‘: [‘Ankit‘, ‘Amit‘, ‘Aishwarya‘, ‘Priyanka‘, ‘Priya‘, ‘Shaurya‘ ], 
‘Age‘: [21, 19, 20, 18, 17, 21], 
‘Stream‘: [‘Math‘, ‘Commerce‘, ‘Science‘, ‘Math‘, ‘Math‘, ‘Science‘], 
‘Percentage‘: [88, 92, 95, 70, 65, 78]} 

# create a dataframe 
dataframe = pd.DataFrame(record, columns = [‘Name‘, ‘Age‘, ‘Stream‘, ‘Percentage‘]) 

print("Given Dataframe :\n", dataframe) 

# selecting rows based on condition 
rslt_df = dataframe.loc[dataframe[‘Percentage‘] != 95] 

print(‘\nResult dataframe :\n‘, rslt_df)

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使用`isin()`数据框的方法选择列值存在于列表中的那些行。

代码1：使用基本方法，从给定数据框中选择选项列表中存在‘Stream‘的所有行。

# importing pandas 
import pandas as pd 

record = { 
‘Name‘: [‘Ankit‘, ‘Amit‘, ‘Aishwarya‘, ‘Priyanka‘, ‘Priya‘, ‘Shaurya‘ ], 
‘Age‘: [21, 19, 20, 18, 17, 21], 
‘Stream‘: [‘Math‘, ‘Commerce‘, ‘Science‘, ‘Math‘, ‘Math‘, ‘Science‘], 
‘Percentage‘: [88, 92, 95, 70, 65, 78]} 

# create a dataframe 
dataframe = pd.DataFrame(record, columns = [‘Name‘, ‘Age‘, ‘Stream‘, ‘Percentage‘]) 

print("Given Dataframe :\n", dataframe) 

options = [‘Math‘, ‘Commerce‘] 

# selecting rows based on condition 
rslt_df = dataframe[dataframe[‘Stream‘].isin(options)] 

print(‘\nResult dataframe :\n‘, rslt_df)

技术图片

代码2：使用选择从给定数据帧中选项列表中存在‘Stream‘的所有行loc[]。

# importing pandas 
import pandas as pd 

record = { 
‘Name‘: [‘Ankit‘, ‘Amit‘, ‘Aishwarya‘, ‘Priyanka‘, ‘Priya‘, ‘Shaurya‘ ], 
‘Age‘: [21, 19, 20, 18, 17, 21], 
‘Stream‘: [‘Math‘, ‘Commerce‘, ‘Science‘, ‘Math‘, ‘Math‘, ‘Science‘], 
‘Percentage‘: [88, 92, 95, 70, 65, 78]} 

# create a dataframe 
dataframe = pd.DataFrame(record, columns = [‘Name‘, ‘Age‘, ‘Stream‘, ‘Percentage‘]) 

print("Given Dataframe :\n", dataframe) 

options = [‘Math‘, ‘Commerce‘] 

# selecting rows based on condition 
rslt_df = dataframe.loc[dataframe[‘Stream‘].isin(options)] 

print(‘\nResult dataframe :\n‘, rslt_df)

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代码3：使用选择从给定数据帧中选项列表中不存在‘Stream‘的所有行.loc[]。

# importing pandas 
import pandas as pd 

record = { 
‘Name‘: [‘Ankit‘, ‘Amit‘, ‘Aishwarya‘, ‘Priyanka‘, ‘Priya‘, ‘Shaurya‘ ], 
‘Age‘: [21, 19, 20, 18, 17, 21], 
‘Stream‘: [‘Math‘, ‘Commerce‘, ‘Science‘, ‘Math‘, ‘Math‘, ‘Science‘], 
‘Percentage‘: [88, 92, 95, 70, 65, 78]} 

# create a dataframe 
dataframe = pd.DataFrame(record, columns = [‘Name‘, ‘Age‘, ‘Stream‘, ‘Percentage‘]) 

print("Given Dataframe :\n", dataframe) 

options = [‘Math‘, ‘Science‘] 

# selecting rows based on condition 
rslt_df = dataframe.loc[~dataframe[‘Stream‘].isin(options)] 

print(‘\nresult dataframe :\n‘, rslt_df)

技术图片

使用`‘&‘`运算符根据多个列条件选择行。

代码1： 使用基本方法，从给定数据框中选择‘Age‘等于21并且‘Stream‘出现在选项列表中的所有行。

# importing pandas 
import pandas as pd 

record = { 
‘Name‘: [‘Ankit‘, ‘Amit‘, ‘Aishwarya‘, ‘Priyanka‘, ‘Priya‘, ‘Shaurya‘ ], 
‘Age‘: [21, 19, 20, 18, 17, 21], 
‘Stream‘: [‘Math‘, ‘Commerce‘, ‘Science‘, ‘Math‘, ‘Math‘, ‘Science‘], 
‘Percentage‘: [88, 92, 95, 70, 65, 78]} 

# create a dataframe 
dataframe = pd.DataFrame(record, columns = [‘Name‘, ‘Age‘, ‘Stream‘, ‘Percentage‘]) 

print("Given Dataframe :\n", dataframe) 

options = [‘Math‘, ‘Science‘] 

# selecting rows based on condition 
rslt_df = dataframe[(dataframe[‘Age‘] == 21) & 
        dataframe[‘Stream‘].isin(options)] 

print(‘\nResult dataframe :\n‘, rslt_df)

输出：

技术图片

代码2：使用.loc []从给定数据框中选择所有行，其中‘Age‘等于21，并且‘Stream‘出现在选项列表中。

# importing pandas 
import pandas as pd 

record = { 
‘Name‘: [‘Ankit‘, ‘Amit‘, ‘Aishwarya‘, ‘Priyanka‘, ‘Priya‘, ‘Shaurya‘ ], 
‘Age‘: [21, 19, 20, 18, 17, 21], 
‘Stream‘: [‘Math‘, ‘Commerce‘, ‘Science‘, ‘Math‘, ‘Math‘, ‘Science‘], 
‘Percentage‘: [88, 92, 95, 70, 65, 78]} 

# create a dataframe 
dataframe = pd.DataFrame(record, columns = [‘Name‘, ‘Age‘, ‘Stream‘, ‘Percentage‘]) 

print("Given Dataframe :\n", dataframe) 

options = [‘Math‘, ‘Science‘] 

# selecting rows based on condition 
rslt_df = dataframe.loc[(dataframe[‘Age‘] == 21) & 
            dataframe[‘Stream‘].isin(options)] 

print(‘\nResult dataframe :\n‘, rslt_df)