How to change data types "object" in Pandas dataframe after importing a CSV?
During reading a csv file:
Use dtype or converters attribute in read_csv in pandas
import pandas as pd
import numpy as np
df = pd.read_csv('data.csv',dtypes = {'a':float64,'b':int32},headers=None)
Here,automatically the types will be read as the datatype you specified.
After having read the csv file:
Use astype function to change the column types.
Check this code.
Consider you have two columns
df[['a', 'b']] = df[['a', 'b']].astype(float)
The advantage of this is you change type of multiple columns at once.
I have imported a CSV file as a Pandas dataframe. When I run df.dtypes I get most columns as "object", which is useless for taking into Bokeh for charts.

I need to change a column as int, another column as date, and the rest as strings.
I see the data types only once I import it.  Would you recommend changing it during import (how?), or after import?