convert whole List from Float to integer in Pandas

Question

Im new to Pandas. I have fetched some values from the database, created a dataframe and used this dataframe to create a pivot table. The problem i am facing is, that if i loop through the list, the integer values are per default floats. I want them to be integers.

so here is my code:

resTable = cur.fetchall()
colNames = cur.column_names


df = pd.DataFrame(resTable, columns = colNames)

result = dfTable.to_json(orient='split')
jsonResult = json.loads(result)


dataTable = jsonResult['data']

for dt in dataTable:
    print(dt)

the results i got from this loop are the following:

[1.0, 1.0, 1.0]

[1.0, 1.0, 1.0]

[1.0, 1.0, 1.0]

[None, 1.0, None]

is there a way to parse each value to integer in pandas? or to set the default to integer? Thank you for help

Answer 1

use apply and pandas.to_numeric to convert your values and replace NaN values using astype(int), for example:

import pandas as pd

df=pd.DataFrame([[1.0, 1.0, 1.0],[1.0, 1.0, 1.0],[1.0, 1.0, 1.0],[None, 1.0, None]], columns=['a','b','c'])
df=df.apply(pd.to_numeric, errors="ignore")
df.fillna(0).astype(int)

Output

     a    b    c
0  1.0  1.0  1.0
1  1.0  1.0  1.0
2  1.0  1.0  1.0
3  NaN  1.0  NaN