使用其他数据框中的匹配值在数据框中创建新列

本文介绍了使用其他数据框中的匹配值在数据框中创建新列的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

有两个数据帧，一个具有很少的信息(df1)，另一个具有所有数据(df2).我正在df1的新列中尝试创建的内容，该列查找Total2值并根据名称"相应地填充新列.请注意，在df1中可见的名称将始终在df2的名称中找到匹配项.我想知道熊猫中是否已经有一些功能可以做到这一点?我的最终目标是创建一个条形图.

Have two dataframes, one has few information (df1) and other has all data (df2). What I am trying to create in a new column in df1 that finds the Total2 values and populates the new column accordingly based on the Names. Note that the Names visible in df1 will always find a match in Names of df2. I am wondering if there is some function in Pandas that already does this? My end goal is to create a bar chart.

alldatapath = "all_data.csv" filteredpath = "filtered.csv" import pandas as pd df1 = pd.read_csv( filteredpath, # file name sep=',', # column separator quotechar='"', # quoting character na_values="NA", # fill missing values with 0 usecols=[0,1], # columns to use decimal='.') # symbol for decimals df2 = pd.read_csv( alldatapath, # file name sep=',', # column separator quotechar='"', # quoting character na_values="NA", # fill missing values with 0 usecols=[0,1], # columns to use decimal='.') # symbol for decimals df1 = df1.head(5) #trim to top 5 print(df1) print(df2)

输出(df1):

Name Total 0 Accounting 3 1 Reporting 1 2 Finance 1 3 Audit 1 4 Template 2

输出(df2):

Name Total2 0 Reporting 100 1 Accounting 120 2 Finance 400 3 Audit 500 4 Information 50 5 Template 1200 6 KnowHow 2000

最终输出(df1)应该类似于:

Final Output (df1) should be something like:

Name Total Total2(new column) 0 Accounting 3 120 1 Reporting 1 100 2 Finance 1 400 3 Audit 1 500 4 Template 2 1200

推荐答案

需要 map 首先由Series表示新列:

df1['Total2'] = df1['Name'].map(df2.set_index('Name')['Total2']) print (df1) Name Total Total2 0 Accounting 3 120 1 Reporting 1 100 2 Finance 1 400 3 Audit 1 500 4 Template 2 1200

然后 set_index 与 DataFrame.plot.bar :

df1.set_index('Name').plot.bar()