Roller-Coaster-Data-Visualization-Project-/script.py at master · Ajay0511/Roller-Coaster-Data-Visualization-Project- · 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
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
import codecademylib3_seaborn
import pandas as pd
import matplotlib.pyplot as plt

# load rankings data here:


wood_rankings = pd.read_csv('Golden_Ticket_Award_Winners_Wood.csv')
steel_rankings = pd.read_csv('Golden_Ticket_Award_Winners_Steel.csv')
print(wood_rankings.head())
print(steel_rankings.head())


# write function to plot rankings over time for 1 roller coaster here:
def plotting_one(coaster_name, park_name, rankings_df):
    coaster_rankings = rankings_df[(rankings_df['Name'] == coaster_name)]
    fig, ax = plt.subplots()
    ax.plot(coaster_rankings['Year of Rank'], coaster_rankings['Rank'])
    ax.set_yticks(coaster_rankings['Rank'].values)
    ax.set_xticks(coaster_rankings['Year of Rank'].values)
    ax.invert_yaxis()
    plt.title("{} Rankings".format(coaster_name))
    plt.xlabel('Year')
    plt.ylabel('Ranking')
    plt.show()


plotting_one('El Toro', 'Six Flags Great Adventure', wood_rankings)

plt.clf()


# write function to plot rankings over time for 2 roller coasters here:
def plotting_two(coaster_1_name, park_1_name, coaster_2_name, park_2_name, rankings_df):
    coaster_1_rankings = rankings_df[(rankings_df['Name'] == coaster_1_name) & (rankings_df['Park'] == park_1_name)]
    coaster_2_rankings = rankings_df[(rankings_df['Name'] == coaster_2_name) & (rankings_df['Park'] == park_2_name)]
    fig, ax = plt.subplots()
    ax.plot(coaster_1_rankings['Year of Rank'], coaster_1_rankings['Rank'], color='green', label=coaster_1_name)
    ax.plot(coaster_2_rankings['Year of Rank'], coaster_2_rankings['Rank'], color='red', label=coaster_2_name)
    ax.invert_yaxis()
    plt.title("{} vs {} Rankings".format(coaster_1_name, coaster_2_name))
    plt.xlabel('Year')
    plt.ylabel('Ranking')
    plt.legend()
    plt.show()


plotting_two('El Toro', 'Six Flags Great Adventure', 'Boulder Dash', 'Lake Compounce', wood_rankings)

plt.clf()


# write function to plot top n rankings over time here:
def plotting_n(rankings_df, n):
    top_n_rankings = rankings_df[rankings_df['Rank'] <= n]
    fig, ax = plt.subplots(figsize=(10, 10))
    for coaster in set(top_n_rankings['Name']):
        coaster_rankings = top_n_rankings[top_n_rankings['Name'] == coaster]
        ax.plot(coaster_rankings['Year of Rank'], coaster_rankings['Rank'], label=coaster)
    ax.set_yticks([i for i in range(1, 6)])
    ax.invert_yaxis()
    plt.title("Top 10 Rankings")
    plt.xlabel('Year')
    plt.ylabel('Ranking')
    plt.legend(loc=4)
    plt.show()


roller_coasters = pd.read_csv('roller_coasters.csv')


# print(roller_coasters.head())

# function to plot histogram of column values
def plot_histogram(coaster_df, column_name):
    plt.hist(coaster_df[column_name].dropna())
    plt.title('Histogram of Roller Coaster {}'.format(column_name))
    plt.xlabel(column_name)
    plt.ylabel('Count')
    plt.show()


plot_histogram(roller_coasters, 'speed')
plt.clf()
plot_histogram(roller_coasters, 'length')
plt.clf()
plot_histogram(roller_coasters, 'num_inversions')
plt.clf()


def plotting_inversions_by_heights(coaster_df, park_name):
    park_coasters = coaster_df[coaster_df['park'] == park_name]
    park_coasters = park_coasters.sort_values('num_inversions', ascending=False)
    coaster_names = park_coasters['name']
    number_inversions = park_coasters['num_inversions']
    plt.bar(range(len(number_inversions)), number_inversions)
    ax = plt.subplot()
    ax.set_xticks(range(len(coaster_names)))
    ax.set_xticklabels(coaster_names, rotation=90)
    plt.title('Number of Inversions Per Coaster at {}'.format(park_name))
    plt.xlabel('Roller Coaster')
    plt.ylabel('# of Inversions')
    plt.show()


plotting_inversions_by_heights(roller_coasters, 'Six Flags Great Adventure')
plt.clf()


# write function to plot pie chart of operating status here:

def piechart(coaster_df):
    operating_coasters = coaster_df[coaster_df['status'] == 'status.operating']
    closed_coasters = coaster_df[coaster_df['status'] == 'status.closed.definitely']
    num_operating_coasters = len(operating_coasters)
    num_closed_coasters = len(closed_coasters)
    status_counts = [num_operating_coasters, num_closed_coasters]
    plt.pie(status_counts, autopct='%0.1f%%', labels=['Operating', 'Closed'])
    plt.axis('equal')
    plt.show()


piechart(roller_coasters)

plt.clf()


# write function to create scatter plot of any two numeric columns here:


def plot_scatter(coaster_df, column_x, column_y):
    plt.scatter(coaster_df[column_x], coaster_df[column_y])
    plt.title('Scatter Plot of {} Vs {}'.format(column_y, column_x))
    plt.xlabel(column_x)
    plt.ylabel(column_y)
    plt.show()


def plot_scatter_height_speed(coaster_df):
    coaster_df = coaster_df[coaster_df['height'] < 140]
    plt.scatter(coaster_df['height'], coaster_df['speed'])
    plt.title('Scatter Plot of Speed vs. Height')
    plt.xlabel('Height')
    plt.ylabel('Speed')
    plt.show()


plt.clf()