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?

• roganjosh: 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?
• Marima: @roganjosh Oh right!! stupid mistake . thanks it worked !!

Answer 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', ...]).

• MaxU - stand with Ukraine: 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...
• coldspeed95: @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: @cᴏʟᴅsᴘᴇᴇᴅ, please feel free to edit your answer ... ;-)