CODEWITHSUNDEEP
pythonpython-3.xpandasdataframe
Emin
Emin

Reputation: 11

ValueError: invalid literal for int() with base 10: '' in Python/ IndexError: list index out of range

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I'm trying to learn Python and I'm working on a project. I want to split a column. Column like this; income 60-80 120- 0-40 Here is my code: For def["min_income] line, I get invalid literal for int() with base error, for the other line (max_income) I receive list index out of range error.

income = df["Income"]
income = income.replace({"Unknown": ""})

df["min_income"] = income.apply(lambda x: int(x.split("-")[0]))
df["max_income"] = income.apply(lambda x: x.split("-")[1])

But the outcome give an error like this:

 df["min_income"] = income.apply(lambda x: int(x.split("-")[0]))
Traceback (most recent call last):

  File "<ipython-input-69-9be6a45724ad>", line 1, in <module>
    df["min_income"] = income.apply(lambda x: int(x.split("-")[0]))

  File "C:\Users\memin\anaconda3\lib\site-packages\pandas\core\series.py", line 4138, in apply
    mapped = lib.map_infer(values, f, convert=convert_dtype)

  File "pandas\_libs\lib.pyx", line 2467, in pandas._libs.lib.map_infer

  File "<ipython-input-69-9be6a45724ad>", line 1, in <lambda>
    df["min_income"] = income.apply(lambda x: int(x.split("-")[0]))

ValueError: invalid literal for int() with base 10: ''

I want to split the income column into two different parts(columns)-min_income and max_income- as integer form. I check the error in the internet but I could not fix the problem. How can I solve this problem? Also I tired .astype(int) func.

Upvotes: 1

Views: 985

Answers (1)

Andrej Kesely
Andrej Kesely

Reputation: 195418

If you have this dataframe:

   income
0   60-80
1    0-40
2    120-
3  80-120
4    -255

Then:

df[["min_income", "max_income"]] = df["income"].str.split("-", expand=True)
print(df)

Will create two columns "min_income" and "max_income":

   income min_income max_income
0   60-80         60         80
1    0-40          0         40
2    120-        120           
3  80-120         80        120
4    -255                   255

You then can fill the blank values as you wish (and then convert to numeric format).

Upvotes: 0

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