Series Object

The pandas series object
    the base data structure of pandas is the sereis object,which is 
    designed to operate similar to a numpy array but also add index         capablilities 
import pandas as pd
from pandas import Series
s = Series([1, 2, 3, 4]) #create a four item
s
s[[1, 3]] #return a series with the rows with labels 1 and 3
1    2
3    4
dtype: int64

s = Series([1, 2, 3, 4],
          index = ['a', 'b', 'c', 'd']) #create a item with index
s
a    1
b    2
c    3
d    4
dtype: int64

s[['a', 'd']]
a    1
d    4
dtype: int64

s.index #it will show index
Index(['a', 'b', 'c', 'd'], dtype='object')

s.values #it will show values
array([1, 2, 3, 4])

dates = pd.date_range('2019-05-18', '2019-05-25')
dates
DatetimeIndex(['2019-05-18', '2019-05-19', '2019-05-20', '2019-05-21',
               '2019-05-22', '2019-05-23', '2019-05-24', '2019-05-25'],
              dtype='datetime64[ns]', freq='D')

temp_chennai = Series([36, 37, 36, 37, 37, 37, 37, 37],
                     index = dates)
temp_delhi = Series([34, 39, 41, 41, 41, 41, 41, 42],
                   index = dates)
temp_chennai.mean()
36.75

temp_delhi.mean()
40.0

temp_diffs_between_chennai_and_delhi = abs(temp_delhi - temp_chennai)
temp_diffs_between_chennai_and_delhi
2019-05-18    2
2019-05-19    2
2019-05-20    5
2019-05-21    4
2019-05-22    4
2019-05-23    4
2019-05-24    4
2019-05-25    5
Freq: D, dtype: int64

temp_diffs_between_chennai_and_delhi['2019-05-20']
5