Adding two Series with NaNs

Question

I\'m working through the \"Python For Data Analysis\" and I don\'t understand a particular functionality. Adding two pandas series objects will automatically align the index

Answer 1

It makes more sense to use pd.concat() as it can accept more columns.

import pandas as pd
import numpy as np

a = pd.Series([35000,71000,16000,5000],index=['Ohio','Texas','Oregon','Utah'])
b = pd.Series([np.nan,71000,16000,35000],index=['California', 'Texas', 'Oregon', 'Ohio'])

pd.concat((a,b), axis=1).sum(1, min_count=1)

Output:

California         NaN
Ohio           70000.0
Oregon         32000.0
Texas         142000.0
Utah            5000.0
dtype: float64

---

Or with 3 series:

import pandas as pd
import numpy as np

a = pd.Series([1, np.NaN, 4, 5])
b = pd.Series([3, np.NaN, 5, np.NaN])
c = pd.Series([np.NaN,np.NaN,np.NaN,np.NaN])

print(pd.concat((a,b,c), axis=1).sum(1, min_count=1))

#0    4.0
#1    NaN
#2    9.0
#3    5.0
#dtype: float64