I have a dataframe with string columns some of them are numbers in string and some others are just string. I want to convert the columns that are numbers in floats but not string. Someone sent me a link but it works only if you know the column and my dataframe is flexible.
>>> df_1
A B C
2 M01 test '100.0'
3 M02 test2 '80.0'
Convert a string that contains a price with space after thousands to float in pandas column
Hope this helps:
>>> data = {'A': {2: 'M01', 3: 'M02'},
'B': {2: 'test', 3: 'test2'},
'C': {2: '100.0', 3: '80.0'}}
>>> df = pd.DataFrame(data)
>>> df.dtypes
A object
B object
C object
dtype: object
>>> df = df.apply(pd.to_numeric, errors='ignore')
>>> df.dtypes
A object
B object
C float64
dtype: object
You can use this:
import pandas as pd
data = {'A':['M01', 'M02'],'B':['test','test2'], 'C': ['100.0', '80.0']}
df = pd.DataFrame(data)
#find columns which are numbers
m = df.apply(lambda s: pd.to_numeric(s, errors='coerce').notnull().all())
#convert True columns in `m` to float
for col in df.columns:
if m[col]:
df[col] = df[col].astype({col: 'float'})
df.dtypes
Output:
A object
B object
C float64
dtype: object
