CODEWITHSUNDEEP
pythonpython-3.xpandasdata-science
Chris90
Chris90

Reputation: 1998

Convert object data type column to integer error

I have a df with a column that I want to filter for only negative or only positve values,

when I try code below as:

df.loc[df['values'] > 0]

I get error of

`TypeError: '>' not supported between instances of 'str' and 'int'

I try to convert the object data type of the values column to integer:

df['values'].astype(str).astype(int)

I get error of : ValueError: invalid literal for int() with base 10: '3.69'

Thanks!

How Can I convert correctly so I can then filter correctly? Thanks!

Upvotes: 1

Views: 104

Answers (2)

Mehdi Golzadeh
Mehdi Golzadeh

Reputation: 2583

If you want to convert it to int you should use apply function:

df = df.assign(values = lambda x: x['values'].apply(lambda s: int(s)))

Upvotes: 0

Cameron Riddell
Cameron Riddell

Reputation: 13447

You need to convert it to a float dtype since 3.69 is a decimal (and therefore a float). int datatypes can only non-decimal numbers (e.g. 1, 2, 4, 100, 900). Try this:

df.loc[df['values'].astype(float) > 0]

Upvotes: 2

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