stemgraphic quickstart with categorical

Import stem_graphic from stemgraphic.alpha



In [1]:

    
%matplotlib inline
import pandas as pd
from stemgraphic.alpha import stem_graphic

Load a data frame



In [2]:

    
df = pd.read_csv('../iris.csv')



In [3]:

    
df.describe(include='all')









    Out[3]:







  
    
      
      sepal_length
      sepal_width
      petal_length
      petal_width
      species
    
  
  
    
      count
      150.000000
      150.000000
      150.000000
      150.000000
      150
    
    
      unique
      NaN
      NaN
      NaN
      NaN
      3
    
    
      top
      NaN
      NaN
      NaN
      NaN
      versicolor
    
    
      freq
      NaN
      NaN
      NaN
      NaN
      50
    
    
      mean
      5.843333
      3.054000
      3.758667
      1.198667
      NaN
    
    
      std
      0.828066
      0.433594
      1.764420
      0.763161
      NaN
    
    
      min
      4.300000
      2.000000
      1.000000
      0.100000
      NaN
    
    
      25%
      5.100000
      2.800000
      1.600000
      0.300000
      NaN
    
    
      50%
      5.800000
      3.000000
      4.350000
      1.300000
      NaN
    
    
      75%
      6.400000
      3.300000
      5.100000
      1.800000
      NaN
    
    
      max
      7.900000
      4.400000
      6.900000
      2.500000
      NaN

Select a column with text.



In [4]:

    
stem_graphic(list(df['species'].values));

From this, we see we have 50 setosa, 50 versicolor and 50 virginica, but you probably already knew that!



In [ ]:

	sepal_length	sepal_width	petal_length	petal_width	species
count	150.000000	150.000000	150.000000	150.000000	150
unique	NaN	NaN	NaN	NaN	3
top	NaN	NaN	NaN	NaN	versicolor
freq	NaN	NaN	NaN	NaN	50
mean	5.843333	3.054000	3.758667	1.198667	NaN
std	0.828066	0.433594	1.764420	0.763161	NaN
min	4.300000	2.000000	1.000000	0.100000	NaN
25%	5.100000	2.800000	1.600000	0.300000	NaN
50%	5.800000	3.000000	4.350000	1.300000	NaN
75%	6.400000	3.300000	5.100000	1.800000	NaN
max	7.900000	4.400000	6.900000	2.500000	NaN