Given this data frame:
import pandas as pd
d=pd.DataFrame({'A':['a','b',99],'B':[1,2,'99'],'C':['abcd99',4,5]})
d
A B C
0 a 1 abcd*
1 b 2 4
2 99 99 5
I want to replace all 99s in the entire data frame with asterisks. I've tried this:
d.replace('99','*')
...but it only worked in the case of the string 99 in column B.
Thanks in advance!
This will do the job:
import pandas as pd
d=pd.DataFrame({'A':['a','b',99],'B':[1,2,'99'],'C':['abcd99',4,5]})
d=d.astype(str)
d.replace('99','*',regex=True)
which gives
A B C
0 a 1 abcd*
1 b 2 4
2 * * 5
Note that this creates a new dataframe. You can also do that inplace instead:
d.replace('99','*',regex=True,inplace=True)
If you want to replace all the 99s , try using regex
>>> d.astype(str).replace('99','*',regex=True)
A B C
0 a 1 abcd*
1 b 2 4
2 * * 5
Use numpys character functions
d.values[:] = np.core.defchararray.replace(d.values.astype(str), '99', '*')
d
A B C
0 a 1 abcd*
1 b 2 4
2 * * 5
naive time test
Problem is values 99 in column A and B are of different types:
>>> type(d.loc[2,"A"])
<class 'int'>
>>> type(d.loc[2,"B"])
<class 'str'>
You can cast your dataframe to string type via df.astype() and then replace, resulting in:
>>> d.astype(str).replace("99","*")
A B C
0 a 1 abcd99
1 b 2 4
2 * * 5
Edit: using regex is the correct solution as given by other answers. I for some reason missed the abcd* in your DataFrame.
Will leave this here, just in case it is helpful to someone else.
