pandas 使用来自其他数据帧的匹配值在数据帧中创建新列
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Create new column in dataframe with match values from other dataframe
提问by Gonzalo
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.
有两个数据帧，一个有很少的信息（df1），另一个有所有数据（df2）。我试图在 df1 中的一个新列中创建什么，该列查找 Total2 值并根据名称相应地填充新列。请注意，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 Pandas 中是否有一些功能已经做到了这一点？我的最终目标是创建一个条形图。
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)
output (df1):
输出（df1）：
Name Total
0 Accounting 3
1 Reporting 1
2 Finance 1
3 Audit 1
4 Template 2
output (df2):
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
Final Output (df1) should be something like:
最终输出 (df1) 应该是这样的：
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
回答by jezrael
Need mapby Seriesfirst for new column:
需要map通过Series首先为新列：
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
And then set_indexwith DataFrame.plot.bar:
然后set_index用DataFrame.plot.bar：
df1.set_index('Name').plot.bar()
