CODEWITHSUNDEEP
pandas
user77005
user77005

Reputation: 1849

pandas read_csv() for multiple delimiters

I have a file which has data as follows

1000000 183:0.6673;2:0.3535;359:0.304;363:0.1835
1000001 92:1.0
1000002 112:1.0
1000003 154435:0.746;30:0.3902;220:0.2803;238:0.2781;232:0.2717
1000004 118:1.0
1000005 157:0.484;25:0.4383;198:0.3033
1000006 277:0.7815;1980:0.4825;146:0.175
1000007 4069:0.6678;2557:0.6104;137:0.4261
1000009 2:1.0

I want to read the file to a pandas dataframe seperated by the multiple delimeters \t, :, ;

I tried

df_user_key_word_org = pd.read_csv(filepath+"user_key_word.txt", sep='\t|:|;', header=None, engine='python')

It gives me the following error.

pandas.errors.ParserError: Error could be due to quotes being ignored when a multi-char delimiter is used.

Why am I getting this error?

So I thought I'll try to use the regex string. But I am not sure how to write a split regex. r'\t|:|;' doesn't work.

What is the best way to read a file to a pandas data frame with multiple delimiters?

Upvotes: 19

Views: 63099

Answers (1)

Tai
Tai

Reputation: 7994

From this question, Handling Variable Number of Columns with Pandas - Python, one workaround to pandas.errors.ParserError: Expected 29 fields in line 11, saw 45. is let read_csv know about how many columns in advance.

my_cols = [str(i) for i in range(45)] # create some col names
df_user_key_word_org = pd.read_csv(filepath+"user_key_word.txt",
                                   sep="\s+|;|:",
                                   names=my_cols, 
                                   header=None, 
                                   engine="python")
# I tested with s = StringIO(text_from_OP) on my computer

enter image description here

Hope this works.

Upvotes: 20

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