CODEWITHSUNDEEP
pythonpandaspython-2.7joininner-join
Veljko
Veljko

Reputation: 1808

Python 2.7 - merge two CSV files without headers and with two delimiters in the first file

I have one csv test1.csv (I do not have headers in it!!!). I also have as you can see delimiter with pipe but also with exactly one tab after the eight column.

ug|s|b|city|bg|1|94|ON-05-0216  9.72|28|288
ug|s|b|city|bg|1|94|ON-05-0217  9.72|28|288

I have second file test2.csv with only delimiter pipe

ON-05-0216|100|50
ON-05-0180|244|152
ON-05-0219|269|146

So because only one value (ON-05-0216) is being matched from the eight column from the first file and first column from the second file it means that I should have only one value in output file, but with addition of SUM column from the second and third column from second file (100+50).

So the final result is the following:

ug|s|b|city|bg|1|94|ON-05-0216  Total=150|9.72|28|288

or 

ug|s|b|city|bg|1|94|ON-05-0216|Total=150    9.72|28|288

whatever is easier.

I though that the best way to use is with pandas. But I stuck with taking multiple delimiters from the first file and how to match columns without column names, so not sure how to continue further.

import pandas as pd

a = pd.read_csv("test1.csv", header=None)
b = pd.read_csv("test2.csv", header=None)
merged = a.merge(b,)
merged.to_csv("output.csv", index=False)

Thank you in advance

Upvotes: 0

Views: 349

Answers (2)

meW
meW

Reputation: 3967

Use:

# Reading files
df1 = pd.read_csv('file1.csv', header=None, sep='|')
df2 = pd.read_csv('file2.csv', header=None, sep='|')

# splitting file on tab and concatenating with rest 
ndf = pd.concat([df1.iloc[:,:7], df1[7].str.split('\t', expand=True), df1.iloc[:,8:]], axis=1)
ndf.columns = np.arange(11)

# adding values from df2 and bringing in format Total=sum
df2.columns = ['c1', 'c2', 'c3']
tot = df2.eval('c2+c3').apply(lambda x: 'Total='+str(x))

# Finding which rows needs to be retained
idx_1 = ndf.iloc[:,7].str.split('-',expand=True).iloc[:,2]
idx_2 = df2.c1.str.split('-',expand=True).iloc[:,2]
idx = idx_1.isin(idx_2)      # Updated
ndf = ndf[idx].reset_index(drop=True)
tot = tot[idx].reset_index(drop=True)

# concatenating both CSV together and writing output csv
ndf.iloc[:,7] = ndf.iloc[:,7].map(str) + chr(9) + tot
pd.concat([ndf.iloc[:,:8],ndf.iloc[:,8:]], axis=1).to_csv('out.csv', sep='|', header=None, index=None)

# OUTPUT
# ug|s|b|city|bg|1|94|ON-05-0216    Total=150|9.72|28|288

Upvotes: 1

Marjan Moderc
Marjan Moderc

Reputation: 2859

You can use pipe as a delimeter when reading csv pd.read_csv(... sep='|'), and only split the tab separated columns later on by using this example here.

When merging two dataframes, you must have a common column that you will merge on. You could use them as index for easier appending after you do the neccessary math on separate dataframes.

Upvotes: 0

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