Wikimedia_Challenge/plotting_functions.py at master · mdh266/Wikimedia_Challenge · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
"""
This contains some functions to make plots that were a little
move involved. They are in this file to save space in the
juptyer notebook.
"""

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt


def plot_grouped_and_ungrouped(diff, rate, string):
    """
    Function that plots the Pandas Series values as bar graph.

    :param: rate (float) : The value of the ungrouped results to
                          be plotted.

    :param: diff (Pandas Series) : The Series is usually the grouped
                                   results.

    :param: string (str) : The description of the value to be plotted.
    """
    plt.figure(figsize=(4, 4))
    diff = diff.append(pd.Series([rate], index=['ungrouped']))
    diff.plot(kind='bar')
    plt.title(string)
    plt.xticks(rotation=0)
    plt.show()


def plot_daily_clicked(first_clicked, top_num):
    """
    Plots bar graphs of the daily number of clicks on the each search
    result by order of the listing.  The x-axis will be the ordering
    of the webpage search result and y-axis is the number of people's
    whose first click was that result_position.  Each bar graph
    represents one of the eight days.

    :param: first_clicked (Pandas Series) : This multi-index series.
            index level 0 - date
            index level 1 - session_id
            values - result_position

    :param: top_num (int): The number of web page clicks.
    """
    days = ['2016-03-01', '2016-03-02', '2016-03-03', '2016-03-04',
            '2016-03-05', '2016-03-06', '2016-03-07', '2016-03-08']

    day = 0
    string = ""
    plt.figure(figsize=(6, 7))
    for j in range(1,9):
        plt.subplot(4,2,j)
        # count the top 20 highest clicked links of this day
        day_clicked =\
            first_clicked[days[day]].value_counts().sort_index().head(top_num)

        plt.bar(day_clicked.index, day_clicked.values)
        plt.ylabel('Count')
        plt.title(days[day],fontsize=10)
        plt.xlabel('Result Position')
        plt.ylim([0,2500])
        day += 1

    plt.tight_layout()
    plt.show()


def plot_session_length_by_group(session_length_by_group):
    """
    Plots the frquency of sessions in group a and group b
    that have a session_length with in certain time inverals
    that were determined beforehand.

    :param: session_length_by_group (Pandas Series) : The frequency
                                        of session length by group.
    """
    plt.figure(figsize=(6,4))
    fig, ax = plt.subplots()
    rects1 = session_length_by_group['a'].sort_index().plot(kind='bar',
                                                        color='b',
                                                        label='Group a')

    rects2 = session_length_by_group['b'].sort_index().plot(kind='bar',
                                                        color='r',
                                                        label='Group b')
    plt.ylabel('Count Of Sessions')
    plt.xlabel('Session Length In Seconds')
    plt.title('Session Length Between The Groups')
    plt.legend()
    plt.show()


def plot_session_length_by_group_percentages(session_length_a,
                                             session_length_b):
    """
    Plots the percentages of sessions in group a and group b
    that had a session_length with in certain time inverals
    that were determined beforehand.


    :param: sesssion_length_a (Pandas Series) :
    :param: sesssion_length_b(Pandas Series) :
    """

    plt.figure(figsize=(9,5))
    plt.subplot(121)
    session_length_a.sort_index().plot(kind='bar',
                                    color='b',
                                    label='Group a')

    plt.title('Percentage Of Sessions By Session Length',
            fontsize=10)

    plt.ylim([0,0.25])
    plt.legend()
    plt.subplot(122)

    rects2 = session_length_b.sort_index().plot(kind='bar',
                                            color='r',
                                            label='Group b')

    plt.title('Percentage Of Sessions By Session Length',
            fontsize=10)

    plt.ylim([0,0.25])
    plt.legend()
    plt.show()