How can I convert t and f values in numeric in python Dataframe?-CodePudding

A  B
t  f
t  t
f  f
t  t

How to convert this kind of data in numeric form in python for multiple columns?

CodePudding user response：

You could replace the values using a dictionary:

df[['A', 'B']] = df[['A', 'B']].replace({ 't': 1, 'f': 0 })

Output:

CodePudding user response：

Use factorize with DataFrame.stack for numeric columns by categories:

cols = ['A','B']

y, label = pd.factorize(df[cols].stack())

df[cols] = y.reshape(df[cols].shape)
print (df)
   A  B
0  0  1
1  0  0
2  1  1
3  0  0

Dictionary for mapping is possible generate by:

d = dict(zip(label, y))
print (d)
{'t': 0, 'f': 1}

CodePudding user response：

the first thing i came to was using factorize, but as it's already given above i came to the second:

df = df.stack().to_frame().apply(lambda x: pd.Categorical(x).codes).unstack().droplevel(0,1)

>>> df
'''
   A  B
0  1  0
1  1  1
2  0  0
3  1  1