I have a data frame with 6 columns. I would like to convert one of the columns (the second one) from float to int, when I do this it only returns the one column as an int but I want the exact same dataframe in its entirety, the only difference is that the second column is int as opposed to float.
I have checked all relevant questions on here and nothing worked for me!! please help
You can do something like this!
>>> df = pd.DataFrame({'num_legs': [2, 4, 8, 0],
'num_wings': [2, 0, 0, 0],
'num_specimen_seen': [10, 2, 1, 8]},
index=['falcon', 'dog', 'spider', 'fish'])
>>> df
num_legs num_wings num_specimen_seen
falcon 2 2 10
dog 4 0 2
spider 8 0 1
fish 0 0 8
>>> df['test'] = df['num_wings'].astype('float')
>>> df
num_legs num_wings num_specimen_seen test
falcon 2 2 10 2.0
dog 4 0 2 0.0
spider 8 0 1 0.0
fish 0 0 8 0.0
You can refer to this link for more details!
It seems like you have a dataframe that looks something like this:
>>> print(df)
c1 c2 c3 c4 c5 c6
0 a 1.0 5 d 20 z
1 b 2.0 6 e 40 y
2 c 3.0 7 f 60 x
I believe you may be using DataFrame.astype to convert your column of floats to a column of ints. Specifically, it seems like you've gotten to this point:
>>> df['c2'].astype(int)
0 1
1 2
2 3
Now, all you need to do is replace the column by calling:
>>> df['c2'] = df['c2'].astype(int)
>>> print(df)
c1 c2 c3 c4 c5 c6
0 a 1 5 d 20 z
1 b 2 6 e 40 y
2 c 3 7 f 60 x
If you'd like to create a new column of ints, you could do this instead:
>>> df['new_col'] = df['c2'].astype(int)
>>> print(df)
c1 c2 c3 c4 c5 c6 new_col
0 a 1.0 5 d 20 z 1
1 b 2.0 6 e 40 y 2
2 c 3.0 7 f 60 x 3
You can reassign to a new column or replace the same column values by
df["col1"] = df["col1"].astype('int32')
astypefunction inpandasmight work here.