Commonly used statistic analysis

import pandas as pd

df1 = pd.read_csv ( "./ data / data1.csv", encoding = 'gbk', index_col = ' Product Code')
Print (df1.head ())
# obtain data
Print (len (DF1))
Print (DF1 .index.size)
# averaging mean median median
Print (DF1 [ 'supplier purchase price'] .mean ())
Print (DF1 [ 'supplier purchase price'] .median ())
# emerge the largest number of public number
from PANDAS Import Series
Data Series = ([7,9,8,9,7,6])
data.mode ()
# most value min (), max ()
Print (df1.min ())
Print (DF1 .max ())
# Range = maximum - minimum
print ( "poor purchase price supplier: {}". format (df1 [ ' supplier purchase price'] .max () - df1 [ ' supplier purchase price' ] .min ()))
# standard deviation: std variance: var
Print ( 'purchase price standard differential supplier: {:. 2f}'. format (df1 [ ' supplier purchase price'] .std ()))
Print ( 'purchase price variance supplier: {:. 2f}' format ( df1 [ ' supplier purchase price'].var ()))
# Statistical analysis Descriptive
statistics = df1.describe ()
#loc, iloc, poor, increase line
statistics.loc [ 'Mean']
statistics.iloc [. 1]
statistics [ 'Range'] = statistics.loc [ 'max'] - statistics.loc [ 'min']

print(statistics)