极客教程根据条件选择pandas DataFrame中的行
让我们看看如何在Pandas DataFrame中根据一些条件来选择行。
使用’>’, ‘=’, ‘=’, ‘<=’, ‘!=’操作符根据特定列的值选择行
代码#1 :使用基本方法从给定的数据框架中选择所有 “百分比 “大于80的行。
# 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)
Python
输出 :
代码#2 :从给定的数据框架中选择所有’百分比’大于80的行，使用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)
Python
输出 :
代码#3 :从给定的数据框架中选择所有’百分比’不等于95的行，使用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)
Python
输出 :
使用数据框架的isin()方法选择那些列值存在于列表中的行
代码#1 :使用基本方法从给定的数据框架中选择所有的行，其中’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', 'Commerce']
# selecting rows based on condition
rslt_df = dataframe[dataframe['Stream'].isin(options)]
print('\nResult dataframe :\n', rslt_df)
Python
输出 :
代码#2 : 使用loc[] 从给定的数据框架中选择所有的行，其中’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', 'Commerce']
# selecting rows based on condition
rslt_df = dataframe.loc[dataframe['Stream'].isin(options)]
print('\nResult dataframe :\n', rslt_df)
Python
输出 :
代码#3 :使用.loc[]从给定的数据框架中选择所有的行，其中’Stream’不在选项列表中。
# 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['Stream'].isin(options)]
print('\nresult dataframe :\n', rslt_df)
Python
输出 :
使用’&’操作符根据多列条件选择行
代码#1 :使用基本方法从给定的数据框架中选择所有行，其中’Age’等于21，’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[(dataframe['Age'] == 21) &
dataframe['Stream'].isin(options)]
print('\nResult dataframe :\n', rslt_df)
Python
输出 :
代码#2 :从给定的数据框架中选择所有行，其中’Age’等于21并且’Stream’出现在选项列表中，使用.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['Age'] == 21) &
dataframe['Stream'].isin(options)]
print('\nResult dataframe :\n', rslt_df)
Python
输出 :
