Converting CSV data to string

Question

So I got a CSV file that has 14 columns, and I was trying to convert that data to string type and I tried this

import pandas as pd
df = pd.read_csv("2008_data_test.csv", sep=",")
output = pd.DataFrame(columns=df.columns)
for c in df.columns:
    if df[c].dtype == object:
        print "convert ", df[c].name, " to string"
        df[c] = df[c].astype(str)
    output.to_csv("2008_data_test.csv_tostring2.csv", index=False)

This gives me the headers only, and I can't figure out what I missed?

Any ideas? And is it possible to convert specific columns?

output = pd.DataFrame(columns=df.columns) is defined before the for loop. That's what you write to CSV; the for loop does basically nothing. Did you mean df.to_csv("2008_data_test.csv_tostring2.csv", index=False) instead? — roganjosh
– roganjosh, Commented Oct 17, 2017 at 19:06

cs95 · Accepted Answer · 2017-10-17 21:03:24Z

1

You're modifying one dataframe, but writing another, that's the reason. Use select_dtypes instead.

c = df.select_dtypes(include=[object]).columns
df[c] = df[c].astype(str)

df.to_csv("2008_data_test.csv_tostring2.csv", index=False)

As MaxU suggested, it might be simpler to do filter by dtypes in this manner:

c = df.columns[df.dtypes.eq('object')]

The former creates a dataframe subslice before accessing columns, so this should be cheaper.

If you want to convert specific columns only, you can remove columns as needed from c before the conversion using c = c.difference(['Col1', 'Col2', ...]).

edited Oct 17, 2017 at 21:03

answered Oct 17, 2017 at 19:09

cs95

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3 Comments

MaxU - stand with Ukraine Over a year ago

I'd use df.columns[df.dtypes.eq('object')] instead of df.select_dtypes(include=[object]).columns as the latter (df.select_dtypes(include=[object])) first generates a DataFrame and then returns its columns...

cs95 Over a year ago

@MaxU that’s great, I didn’t know about that. I’ll edit my answer, or will you write an answer? :)

MaxU - stand with Ukraine Over a year ago

@cᴏʟᴅsᴘᴇᴇᴅ, please feel free to edit your answer ... ;-)

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