Is there a way to convert values like ‘34%’ directly to int or float when using read_csv in pandas? I want ‘34%’ to be directly read as 0.34
-
Using this in
read_csvdid not work:read_csv(..., dtype={'col':np.float}) -
After loading the csv as ‘df’ this also did not work with the error “invalid literal for float(): 34%”
df['col'] = df['col'].astype(float) -
I ended up using this which works but is long winded:
df['col'] = df['col'].apply(lambda x: np.nan if x in ['-'] else x[:-1]).astype(float)/100
Answers:
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Method 1
You were very close with your df attempt. Try changing:
df['col'] = df['col'].astype(float)
to:
df['col'] = df['col'].str.rstrip('%').astype('float') / 100.0
# ^ use str funcs to elim '%' ^ divide by 100
# could also be: .str[:-1].astype(...
Pandas supports Python’s string processing functions on string columns. Just precede the string function you want with .str and see if it does what you need. (This includes string slicing, too, of course.)
Above we utilize .str.rstrip() to get rid of the trailing percent sign, then we divide the array in its entirety by 100.0 to convert from percentage to actual value. For example, 45% is equivalent to 0.45.
Although .str.rstrip('%') could also just be .str[:-1], I prefer to explicitly remove the ‘%’ rather than blindly removing the last char, just in case…
Method 2
You can define a custom function to convert your percents to floats at read_csv() time:
# dummy data
temp1 = """index col
113 34%
122 50%
123 32%
301 12%"""
# Custom function taken from https://stackoverflow.com/questions/12432663/what-is-a-clean-way-to-convert-a-string-percent-to-a-float
def p2f(x):
return float(x.strip('%'))/100
# Pass to `converters` param as a dict...
df = pd.read_csv(io.StringIO(temp1), sep='s+',index_col=[0], converters={'col':p2f})
df
col
index
113 0.34
122 0.50
123 0.32
301 0.12
# Check that dtypes really are floats
df.dtypes
col float64
dtype: object
My percent to float code is courtesy of ashwini’s answer: What is a clean way to convert a string percent to a float?
All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0