What is the Difference in Size and Count in pandas python

Question

I am not understanding at all how it differs?

Answer 1

The major difference is "size" includes NaN values, the "count" does not include NaN. The below example will help you to understand:

df = pd.Dataframe( {"Name":["Nitin", "Sanju", "Manisha", "Manisha", "Sanju" , "Manisha"],

 "City":["Bombay", "Bombay", "Delhi", "Bombay", "Bombay", "Delhi"],

 "Val": [1, 2, 2, np.nan, np.nan, 3]})

df output:

# Output: 
#        City     Name  Val
# 0     Bombay  Nitin   1.0
# 1     Bombay  Sanju   2.0
# 2     Delhi   Manisha 2.0
# 3     Bombay  Manisha NaN
# 4     Bombay  Sanju   NaN
# 5     Delhi   Manisha 3.0

df.groupby(["Name", "City"])['Val'].size().reset_index(name='Size')

# Output: 
#       Name      City  Size
# 0    Nitin   Bombay   1
# 1    Sanju   Bombay   2
# 2    Manisha Delhi    2
# 3    Manisha Delhi    1

df.groupby(["Name", "City"])['Val'].count().reset_index(name='Count')

# Output:

#       Name      City  Size
# 0    Nitin   Bombay   1
# 1    Sanju   Bombay   1
# 2    Manisha Delhi    2
# 3    Manisha Delhi    0

I hope this example works for you.