I have a pandas dataframe that look like this
It is a large dataset with 1500 rows and 200 columns
I was wondering how can I remove the number before each value in row and column. example The values look like this: 1: 0.345 2: -0.467
I want only the value to be like this: 0.345 -0.467
How can I do that?
Select all columns without first by iloc and for each column apply split and select second value of lists by [1], last cast to float:
df = pd.DataFrame({0: ['4,8,7', '7,6'],
1: ['1: 0.345', '1: 0.345'],
2: ['2: -0.467', '2: -0.467']})
print (df)
0 1 2
0 4,8,7 1: 0.345 2: -0.467
1 7,6 1: 0.345 2: -0.467
df.iloc[:, 1:] = df.iloc[:, 1:].apply(lambda x: x.str.split(':').str[1]).astype(float)
print (df)
0 1 2
0 4,8,7 0.345 -0.467
1 7,6 0.345 -0.467
If no NaNs values is possible use cᴏʟᴅsᴘᴇᴇᴅ's solution:
df.iloc[:, 1:] = df.iloc[:, 1:].applymap(lambda x: x.split(':')[-1]).astype(float)
df.iloc[:, 1:] = df.iloc[:, 1:].applymap(lambda x: x.split(':')[-1]).astype(float)