python: change datatype that includes .0

Question

I am working with a dataframe, that unfortunately imports the column "ID" in the following format: 7.350943+e

I thought I fixed the issue with this code:

pd.set_option('display.float_format', lambda x: '%3.f' % x)

However, this only fixes the display, in the back-end it remains in this scientific format.

When I try to create a new column based on column ID and column source, I get the following:

df['Primary_key']=df['ID'].apply(str)+'_'+df['Source'] Name ID Source Primary_key John 782857635 email 782857635.0_email

What format do I need to change the datatype to in order to get rid of the .0?

df['ID'].values array([782929635.0, 783063368.0, 782960457.0, ..., 783257941.0, 783535550.0, nan], dtype=object)

I tried replacing it, in the Primary key, but it didn't work (there was no change to the dataframe)

df['Primary_key']= df['Primary_key'].str.strip().replace(".0_","_")

jas-chu · Accepted Answer · 2017-06-13 18:22:32Z

1

I think you should try something like:

df['ID'] = df['ID'].apply(str).strip().replace(".0","")

answered Jun 13, 2017 at 18:22

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Comments

user6597761 · Accepted Answer · 2017-06-13 18:23:57Z

int() is what you seem to be looking for.

[int(i) for i in whateverList]