根据条件在Pandas DataFrame中选择行

 

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) 

 

输出：

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：

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) 

 

输出：

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) 

 

输出：

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) 

 

输出：

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) 

 

输出：

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：

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) 

输出：