Clean way to convert string containing decimal to a string containing an int for a column in pandas?-CodePudding

I have a dataframe where one column contains numbers but as string values like "1.0", "52.0" etc. I want to convert the column to instead contain strings like "PRE_1", "PRE_52".

Example

df = pd.DataFrame({'pre': ["1.0", "52.0"]})
df["pre"] = 'PRE_'   df["pre"].astype(str)

gives me output of PRE_1.0

I tried: df["pre"] = 'PRE_' df["pre"].astype(int).astype(str) but got a ValueError.

Do I need to convert it into something else before trying to convert it to an int? It looks like: df["pre"].astype(float).astype(int).astype(str) might do what I want but I'm open to cleaner ways of doing it.

I'm pretty new to pandas, so help would be greatly appreciated!

CodePudding user response：

To properly be able to help, having sample data would be great. Based on the information you did provide, if the data coming in is a float, you can apply a format to truncate it as below.

df = pd.DataFrame({'pre': [1.0, 52.0]})
df['pre'] = df['pre'].map('PRE_{:.0f}'.format)
print(df)

CodePudding user response：

Apply a function:

import pandas as pd

df = pd.DataFrame([['1.0'],['52.0']],columns=['Pre'])
print(df)
df.Pre = df.Pre.apply(lambda n: f'PRE_{float(n):.0f}')
print(df)

Output:

    Pre
0   1.0
1  52.0
      Pre
0   PRE_1
1  PRE_52