csv - python pandas read_csv delimiter in column data

Question

I'm having this type of CSV file:

12012;My Name is Mike. What is your's?;3;0 
1522;In my opinion: It's cool; or at least not bad;4;0
21427;Hello. I like this feature!;5;1

I want to get this data into da pandas.DataFrame. But read_csv(sep=";") throws exceptions due to the semicolon in the user generated message column in line 2 (In my opinion: It's cool; or at least not bad). All remaining columns constantly have numeric dtypes.

What is the most convenient method to manage this?

Answer 1

Dealing with unquoted delimiters is always a nuisance. In this case, since it looks like the broken text is known to be surrounded by three correctly-encoded columns, we can recover. TBH, I'd just use the standard Python reader and build a DataFrame once from that:

import csv
import pandas as pd

with open("semi.dat", "r", newline="") as fp:
    reader = csv.reader(fp, delimiter=";")
    rows = [x[:1] + [';'.join(x[1:-2])] + x[-2:] for x in reader] 
    df = pd.DataFrame(rows)

which produces

       0                                              1  2  3
0  12012               My Name is Mike. What is your's?  3  0
1   1522  In my opinion: It's cool; or at least not bad  4  0
2  21427                    Hello. I like this feature!  5  1

Then we can immediately save it and get something quoted correctly:

In [67]: df.to_csv("fixedsemi.dat", sep=";", header=None, index=False)

In [68]: more fixedsemi.dat
12012;My Name is Mike. What is your's?;3;0
1522;"In my opinion: It's cool; or at least not bad";4;0
21427;Hello. I like this feature!;5;1

In [69]: df2 = pd.read_csv("fixedsemi.dat", sep=";", header=None)

In [70]: df2
Out[70]: 
       0                                              1  2  3
0  12012               My Name is Mike. What is your's?  3  0
1   1522  In my opinion: It's cool; or at least not bad  4  0
2  21427                    Hello. I like this feature!  5  1