Convert float64 column to int64 column

Question

I have a csv which has a column that contains a long "ID" string such as 9075841942209708806(int64). Now, when I read this csv file into a pandas data frame, this number turns into -9.191700e+18(float64).

How can the id of -9.191700e+18(float64) be converted in its original form, i.e. 9075841942209708806(int64)?

Oh, I am sorry for the confusion but if the id column is not labelled and thus only column 1 for example, how would that change the code? I tried df = pd.read_csv(file, dtype={'1':np.int64}) but it didnt work...can you help please? — LaLaTi
– LaLaTi, Commented Aug 21, 2018 at 12:49
What about df = pd.read_csv(file, dtype={1:np.int64}, header=None) ? — jezrael
– jezrael, Commented Aug 21, 2018 at 12:51
It somewhat worked. So, now the issue is that the int values do not match anymore with the original ones. For example: original one is 9075841942209708806 and converted one is 9075800000000000000...what can this be due to? — LaLaTi
– LaLaTi, Commented Aug 21, 2018 at 13:04
Hmmm, is possible working with strings? like df = pd.read_csv(file, dtype={1:'str'}, header=None) — jezrael
– jezrael, Commented Aug 21, 2018 at 13:09

alx · Accepted Answer · 2018-08-21 13:27:35Z

2

To change dtype of column you need to use:

 df['ID'] = df['ID'].astype('int64')

Documentation here: LINK

answered Aug 21, 2018 at 13:27

alx

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