group['x-Mean'] = abs(group['Revenue'] - group['Revenue'].mean())
group['1.96*std'] = 1.96*group['Revenue'].std()
group['Outlier'] = abs(group['Revenue'] - group['Revenue'].mean()) > 1.96*group['Revenue'].std()
return group
Newdf = StateMonth.apply(s)
Newdf
# Convert data types
df.Date = df.Date.astype('datetime64')
df.StandardDate = df.StandardDate.astype('datetime64')
df.DateSK = df.DateSK.astype('int')
df.Day = df.Day.astype('int')
df.DOWInMonth = df.DOWInMonth.astype('int')
df.DayOfYear = df.DayOfYear.astype('int')
df.WeekOfYear = df.WeekOfYear.astype('int')
df.WeekOfMonth = df.WeekOfMonth.astype('int')
df.Month = df.Month.astype('int')
df.Quarter = df.Quarter.astype('int')
df.Year = df.Year.astype('int')
print 'Data Types'
print df.dtypes
#From Excel to DataFrame
from pandas import DataFrame, ExcelFile
import pandas as pd
