Python 搜索和附加 2 个 csv 文件

Question

I have 2 CSV files. The first file has a list of all the states in the US but have missing values in the Longitude and Latitude column. I found another CSV file that contains all the longitude and latitude values for all states in the US.

What I want to do now is to loop through the 'Location' column on the first file, match it with the 'Location' column on the 2nd file then get the corresponding values for its Longitude and Latitude. After which, I will need to append these values onto the Longitude and Latitude column in the first file

Currently, what I have is this:

aviationdata = pd.read_csv('AviationData.csv', sep = ',', header = 0, encoding = 'iso-8859-1') #this is the first file
location = pd.read_csv('location.csv') #this is the 2nd file

import csv

with open('location.csv', 'r') as loc:
    locationfile = loc.read()

for i in range(len(aviationdata['Location'])):
    currentlocation = aviationdata['Location'].iloc[i]
    axis = []
    for i in currentlocation:
        if i in aviationdata['Location']:
   ... #i do not know how to continue from here

I do not know how to come up with the codes to compare the location field to extract the longitude and latitude code from location.csv and append them to the longitude and latitude columns accordingly in aviationdata .

These are the fields for the first file (aviationdata)

These are the fields for the 2nd file (location)

Answer 1

this looks like a good job for merge https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.merge.html

Assuming that the Location columns in both DataFrames are exactly the same (that is in terms of case, and spacing) then,

1.) Get all interested columns from Aviation Data

aviationdata = aviationdata[["Location", "Country", "Make", "Weather.Condition", "Year", "Month"]]

2.) Now merge Aviation Data with the currentLocation DataFrame on column name "Location"

aviationdata = aviationdata.merge(currentlocation, on=['Location'])

aviationdata.head(10)