Convert object data type column to integer error

Question

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!

convert it to float (3.69 is a float)

balderman
– balderman

2020-11-02 20:42:27 +00:00
Commented Nov 2, 2020 at 20:42 — balderman
– balderman, Commented Nov 2, 2020 at 20:42

Cameron Riddell · Accepted Answer · 2020-11-02 20:44:00Z

2

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]

answered Nov 2, 2020 at 20:44

Cameron Riddell

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Comments

Mehdi Golzadeh · Accepted Answer · 2020-11-02 20:48:44Z

0

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)))

answered Nov 2, 2020 at 20:48

Mehdi Golzadeh

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