data=pd.read_csv('data.csv') 1. 步骤3:使用set_index方法设置索引列 在pandas中,set_index方法可以用来设置数据框的索引列。假设我们要将索引列设置为"Date"列,可以使用以下代码: data.set_index('Date',inplace=True) 1. 在这里,"Date"是要设置为索引的列名,参数inplace=True表示在原数据框上进行修改。
As we have seen, we can pass column labels of the DataFrame to assign it as an index of the DataFrame. We can also give a list of labels which can be strings or numbers toDataFrame.set_index()function to set a new index in the DataFrame. First, we create a PythonIndexobject from a...
举个例子,有如下的数据集df,df的行索引由index指定,列索引是http_status和response_time: index = ['Firefox','Chrome','Safari','IE10','Konqueror'] df= pd.DataFrame({'http_status': [200, 200, 404, 404, 301],'response_time': [0.04, 0.02, 0.07, 0.08, 1.0]}, index=index) df http_st...
默认为False,表示替换现有索引;如果为True,则将新索引添加到现有索引中。接下来,我们将通过一些代码示例和测试数据集来演示set_index()方法的使用。测试数据集: import pandas as pd data = {'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9]} df = pd.DataFrame(data) print(df) 输出:...
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['c','d'], drop=False)# 2.添加到原有索引df.set_index('c', append=True)# 3.多重索引df.set_index(['c','d'])# 4.修改原数据框df.set_index(['c','d'], inplace=True)# 5.手动指定df.set_index([pd.Index([1,2,3,4,5,6,7]),'c'])# 6.索引计算s = pd.Series([1,2...
set_index()方法的应用示例 首先,我们需要导入pandas库,并创建一个示例DataFrame来演示set_index()方法的使用。 importpandasaspd data={'Name':['Tom','Nick','John','Tom','John'],'Age':[20,21,22,23,24],'Score':[80,85,90,75,95]}df=pd.DataFrame(data)print(df) ...
一、set_index( ) 1、函数体及主要参数解释: DataFrame.set_index(keys,drop=True,append=False,inplace=False,verify_integrity=False) 参数解释: keys:列标签或列标签/数组列表,需要设置为索引的列 drop:默认为True,删除用作新索引的列 append:是否将列附加到现有索引,默认为False。
2.reset_index() 作用:reset_index可以还原索引为普通列,重新变为默认的整形索引 格式:DataFrame.reset_index(level=None, drop=False, inplace=False, col_level=0, col_fill=”) import pandas as pddf = pd.DataFrame({ 'A': ['A0', 'A1', 'A2', 'A3','A4'],'B': ['B0', 'B1', 'B2...
# importing pandas packageimportpandasaspd# making data frame from csv filedata=pd.read_csv("employees.csv")# setting first name as index columndata.set_index("First Name",inplace=True)# displaydata.head() Python Copy 输出: 如输出图片所示,早期的索引列是一系列的数字,但后来被替换成了名字。