def main():
""" Main function """
df_change_platform = project.platform_convert_df(data_frame)
game_type = [
'Home Video Game Consoles', 'Handheld Game Consoles',
'Microsoft Windows'
]
game_in_years = numpy.array(
data_frame.groupby('Year', as_index=False).count()[['Year',
'Rank']]).tolist()
g_in_year = numpy.array(
data_frame.groupby('Year', as_index=False).count()[['Year',
'Rank']]).tolist()
for i in range(len(game_in_years)):
if i == 0:
continue
else:
game_in_years[i][1] += game_in_years[i - 1][1]
game_in_years = project.fill_missing_year(game_in_years)
amount_of_HVGC = pf_count_by_all('Home Video Game Consoles')
amount_of_HHGC = pf_count_by_all('Handheld Game Consoles')
amount_of_MSW = pf_count_by_all('Microsoft Windows')
create_chart(amount_of_HVGC, amount_of_HHGC, amount_of_MSW)
def summed_platform_sales(genre):
""" This Function for Summed Sales of Years in Zone """
data_frame_convert = project.platform_convert_df(data_frame)
genre_sales = []
all_genre_list = numpy.array(
data_frame.groupby(['Year', 'Platform'], as_index=False).sum()[[
'Year', 'Platform', 'Global_Sales'
]]).tolist()
for i in all_genre_list:
selected = [i[0], i[2]]
if i[1] == genre:
genre_sales.append(selected)
return genre_sales
def main():
"""create chart platform type of games count in each year """
data_game = pandas.read_csv('vgsales.csv')
data_game = pj.platform_convert_df(data_game)
data_Year = numpy.array(
data_game.groupby(["Platform", "Year"],
as_index=False).count()[["Platform", "Year",
"Rank"]]).tolist()
data_platform = [
i for i in (data_game.groupby(["Platform"], as_index=False).count()
["Platform"]).tolist()
]
overall = numpy.array(
data_game.groupby(["Year"],
as_index=False).count()[["Year", "Name"]]).tolist()
yearss = numpy.array(
data_game.groupby(["Year"], as_index=False).count()["Year"]).tolist()
data_Year1 = pj.fill_missing_year(overall)
value = []
for i in data_Year1:
value.append(i[1])
chart = pygal.StackedLine(fill=True, interpolate='cubic', dots_size=1.75)
chart.x_labels = range(1980, 2017)
chart.x_labels_major_count = 8
chart.show_minor_x_labels = False
chart.truncate_label = 5
chart.y_labels = [i for i in range(0, 1601, 200)]
chart.y_labels_major_every = 5
chart.legend_at_bottom = True
chart.legend_at_bottom_columns = 3
chart.legend_box_size = 16
chart.x_title = "Year"
chart.y_title = "Video Games Amount"
for i in [
'Home Video Game Consoles', 'Handheld Game Consoles',
'Microsoft Windows'
]:
temp = pj.fill_missing_year([[j[1], j[2]] for j in data_Year
if j[0] == i])
chart.add(i, [j[1] for j in temp])
chart.render_to_file("releases_platform.svg")
def main():
""" Main function """
data_frame = project.platform_convert_df(pandas.read_csv('vgsales.csv'))
create_chart(data_frame)
"""
PSIT Data Analysis Project
Chart: Growth of Video Games Amount
by Supakit Theanthunyakit (POKINBKK)
"""
import pandas, numpy, pygal
from pygal.style import CleanStyle
from project_module import project
data_frame = pandas.read_csv('vgsales.csv')
df_change_platform = project.platform_convert_df(data_frame)
year_pf_list = numpy.array(df_change_platform[['Year', 'Platform']]).tolist()
def main():
""" Main function """
df_change_platform = project.platform_convert_df(data_frame)
game_type = [
'Home Video Game Consoles', 'Handheld Game Consoles',
'Microsoft Windows'
]
game_in_years = numpy.array(
data_frame.groupby('Year', as_index=False).count()[['Year',
'Rank']]).tolist()
g_in_year = numpy.array(
data_frame.groupby('Year', as_index=False).count()[['Year',
'Rank']]).tolist()
for i in range(len(game_in_years)):
if i == 0: