Generating frequency¶

Here we demonstrate how generate frequency table from the data.

Data frame¶

First creates a dataframe, then use value_counts, groupby, crosstab, and `pivot.

import numpy as np
import pandas as pd

n = 50 
group = ["High", "Low"] 
size = ["Small", "Medium", "Large"] 
data = pd.DataFrame({'Size': np.random.choice(size,n), 'Group': np.random.choice(group,n)})

value_counts¶

frq_data=data.value_counts(["Group", "Size"])
frq_data.to_csv('frq_data.csv', sep=',', header=True,index=True, encoding='utf8')

using groupby¶

data.groupby(["Group", "Size"]).size()
data.groupby(["Group", "Size"]).size().reset_index(name="Freq")

crosstab¶

pd.crosstab(data.Group,data.Size,margins = True)
pd.crosstab(data.Group,data.Size,margins = False)

pivot¶

data.pivot_table(index=['Group','Size'], aggfunc='size')

Plot¶

Mosaic plot¶

import matplotlib.pyplot as plt
from statsmodels.graphics.mosaicplot import mosaic
mosaic(data, ["Group", "Size"], title='DataFrame as Source')
plt.show()

Chord Diagram¶

from pycirclize import Circos
matrix_df=pd.DataFrame(pd.crosstab(data.Group,data.Size,margins = False))
circos = Circos.initialize_from_matrix(
    matrix_df,
    space=5,
    cmap="tab10",
    label_kws=dict(size=12),
    link_kws=dict(ec="black", lw=0.5, direction=1),
)
circos.savefig("chroddiagram.png")

list¶

lst = ['apple', 'banana', 'apple', 'orange']

from collections import Counter
Counter(lst)
Counter(data['Group'])

counts = [(word, lst.count(word) / len(lst)) for word in set(lst)] 
[{word: lst.count(word) / len(lst)} for word in set(lst)] 

def relative_frequency(lst, element):
    return lst.count(element) / float(len(lst))