比较两个文件，如果它们都匹配第一列，然后替换第 2 列和第 3 列的值（Python）

Question

There are two files. If the ID number matches both files, then I want only the value 1 and value 2 from File2.txt, Please let me know if my question is unclear

File1.txt


ID Number   Value 1     Value 2     Country 
0001        23            55        Spain
0231        15            23        USA     
4213        10            11        Canada
7541        32            29        Italy

File2.txt

0001        5       6
0231        7       18
4213        54      87
5554        12      10
1111        31      13
6422        66      51

The output should look like this.

ID Number   Value 1     Value 2     Country 
0001          5           6         Spain
0231          7          18         USA     
4213          54         87         Canada
7541          32         29         Italy

New example:

File3.txt

#ID CAT CHN LC SC LATITUDE LONGITUDE 
20022 CX 21 --   4  32.739000  -114.635700 
01711 CX 21 --   3  32.779700  -115.567500
08433 CX 21 --   2  31.919930  -123.321000


File4.txt

20022,32.45,-114.88
01192,32.839,-115.487
01711,32.88,-115.45
01218,32.717,-115.637

output
#ID CAT CHN LC SC LATITUDE LONGITUDE 
20022 CX 21 --   4  32.45  -114.88 
01711 CX 21 --   3  32.88  -115.45
08433 CX 21 --   2  31.919930  -123.321000

Code I got so far

f = open("File3.txt", "r") 
x= open("File4.txt","r")

df1 = pd.read_csv(f, sep=' ', engine='python')
df2 = pd.read_csv(x, sep=' ', header=None, engine='python')

df2 = df2.set_index(0).rename_axis("#ID")
df2 = df2.rename(columns={5:'LATITUDE', 6: 'LONGITUDE'})
df1 = df1.set_index('#ID')
df1.update(df2)
print(df1)

Answer 1

Something like this, possibly:

file1_data = []
file1_headers = []

with open("File1.txt") as file1:
    for line in file1:
        file1_data.append(line.strip().split("\t"))
    file1_headers = file1_data[0]
    del file1_data[0]

file2_data = []

with open("File2.txt") as file2:
    for line in file2:
        file2_data.append(line.strip().split("\t"))

file2_ids = [x[0] for x in file2_data]

final_data = [file1_headers] + file1_data

for i in range(1, len(final_data)):
    if final_data[i][0] in file2_ids:
        match = [x for x in file2_data if x[0] == final_data[i][0]]
        final_data[i] = [match[0] + [final_data[i][3]]]

with open("output.txt", "w") as output:
    output.writelines(["\t".join(x) for x in final_data])

final_data becomes an alias of file1_data and then is selectively replacing rows with matching id's in file2_data , but keeping the country.

Answer 2

Okay, what you need to do here is to get the indexes to match in both dataframes after importing. This is important because pandas use data alignment based on indexes.

Here is a complete example using your data:

from io import StringIO
import pandas as pd

File1txt=StringIO("""ID Number   Value 1     Value 2     Country 
0001        23            55        Spain
0231        15            23        USA     
4213        10            11        Canada
7541        32            29        Italy""")


File2txt = StringIO("""0001        5       6
0231        7       18
4213        54      87
5554        12      10
1111        31      13
6422        66      51""")

df1 = pd.read_csv(File1txt, sep='\s\s+', engine='python')
df2 = pd.read_csv(File2txt, sep='\s\s+', header=None, engine='python')

print(df1)
#    ID Number  Value 1  Value 2 Country
# 0          1       23       55   Spain
# 1        231       15       23     USA
# 2       4213       10       11  Canada
# 3       7541       32       29   Italy

print(df2)
#       0   1   2
# 0     1   5   6
# 1   231   7  18
# 2  4213  54  87
# 3  5554  12  10
# 4  1111  31  13
# 5  6422  66  51

df2 = df2.set_index(0).rename_axis('ID Number')
df2 = df2.rename(columns={1:'Value 1', 2: 'Value 2'})
df1 = df1.set_index('ID Number')
df1.update(df2)
print(df1.reset_index())

Output:

   ID Number  Value 1  Value 2 Country
0          1      5.0      6.0   Spain
1        231      7.0     18.0     USA
2       4213     54.0     87.0  Canada
3       7541     32.0     29.0   Italy