CODEWITHSUNDEEP
pythonpandas
Javi Torre
Javi Torre

Reputation: 824

Avoid importing column as float

I have a column which I want to convert to a string consisting of only 12 digits. For this, I use the below snippet:

# Convert the column to a 12 digit string
df['MY_COLUMN'] = pd.to_numeric(df['MY_COLUMN'], errors='coerce')
df['MY_COLUMN'] = df['MY_COLUMN'].astype(str).str.zfill(12).str.slice(0, 12)

However, my output looks something like this:

16072934175.0
16026886931.0
16089115785.0
16095735607.0
16086482684.0

How could I obtain the same thing but without the final .0?

Expected output:

016072934175
016026886931
016089115785
016095735607
016086482684

Upvotes: 1

Views: 35

Answers (1)

Hamzah Al-Qadasi
Hamzah Al-Qadasi

Reputation: 9786

The main reason why you could not convert it because it is float even after using .astype(str), you can give it a try and check the type of the column after .astype(str). But zfill(12) expects a str type to work not a float.

You can try this example:

df = pd.DataFrame(
    {'c': ['160c','33','c44','99','dd'],
     'd': [1]*5
    }
)

df = df.loc[pd.to_numeric(df['c'], errors='coerce').notna()]
df['c'] = df['c'].astype('str').apply(lambda x: x.zfill(12))

#output

enter image description here

Upvotes: 1

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