how to convert data type of a column in pandas
# You can use "astype" method
# suppose you want to correct your "sales" column data type
df['sales'] = df['sales'].astype('float64')how to convert data type of a column in pandas
# You can use "astype" method
# suppose you want to correct your "sales" column data type
df['sales'] = df['sales'].astype('float64')convert a pandas column to int
# convert Series
my_series = pd.to_numeric(my_series)
# convert column "a" of a DataFrame
df["a"] = pd.to_numeric(df["a"])convert column series to datetime in pandas dataframe
#Converting column to datetime dtype while loading file.
#Create a date parser function
d_parser = lambda x: pd.to_datetime(x)
df = pd.read_csv(file_name.csv, parse_dates=['date_column'], date_parser=d_parser)
#If date is not in parseable format, use
pd.to_datetime.strptime(x, format)
#Eg. format for '2017-03-13 04-PM' is '%Y-%M-%D %I-%p'
#Datetime Formatting Codes - http://bit.ly/python-dt-fmtCopyright © 2021 Codeinu
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