# Erik Rodriguez Video Games Data Analysis and Visualizations, Github Project Notebook and Dataset available https://github.com/AirTechWick/video-games-sales-analysis

import matplotlib.pyplot as plt
import pandas as pd

# Read Data using pandas
vg_sales = pd.read_csv("vgsales_top300.csv")

vg_sales

# Want to see video game sales of GameBoy GB only
gb_games_filter = vg_sales[vg_sales["Platform"] == "GB"] 

# Using the Names of the games as the x labels
categories_x = gb_games_filter["Name"]

# Want to see NA sales as the Y axis values
values_y = gb_games_filter["NA_Sales"] 

# Sorting the NA sales from Most sold to Least sold
sort_values_y = gb_games_filter["NA_Sales"].sort_values(ascending=False)

gb_games_filter

sort_values_y

5      23.20
4      11.27
21     10.83
12      9.00
50      6.16
30      5.89
200     3.40
171     3.02
191     2.71
132     2.55
184     2.49
170     2.18
Name: NA_Sales, dtype: float64

# matplotlib to plot bar graph
plt.bar(categories_x, sort_values_y)

# setting font size
plt.rcParams['font.size'] = 8  

# limiting display of x axis
plt.xlim(0,3)

(0.0, 3.0)

# How frequent each genre is in gba games
freq_genre = plt.hist(gb_games_filter["Genre"])

x_hist_genre = gb_games_filter["Genre"]

from collections import Counter

genre_counts = Counter(x_hist_genre)

plt.pie(genre_counts.values(), labels=genre_counts.keys())

([<matplotlib.patches.Wedge at 0x28a025bbef0>,
  <matplotlib.patches.Wedge at 0x28a02669040>,
  <matplotlib.patches.Wedge at 0x28a0268e4e0>,
  <matplotlib.patches.Wedge at 0x28a02668650>,
  <matplotlib.patches.Wedge at 0x28a0268e900>],
 [Text(0.5499999702695115, 0.9526279613277875, 'Role-Playing'),
  Text(-0.9526279870751434, 0.5499999256737774, 'Puzzle'),
  Text(-0.5499998810780428, -0.9526280128224968, 'Platform'),
  Text(0.7778175867481129, -0.777817331862271, 'Adventure'),
  Text(1.0625184600079092, -0.2847007589424754, 'Misc')])

x_inputs = range(1990,2002)
plt.plot(x_inputs, gb_games_filter["NA_Sales"])

[<matplotlib.lines.Line2D at 0x28a02459e20>]

x_inputs = range(1990,2002)
na_sales = gb_games_filter["NA_Sales"]
eu_sales = gb_games_filter["EU_Sales"]
jp_sales = gb_games_filter["JP_Sales"]

plt.fill_between(x_inputs, na_sales, label="NA Sales")
plt.fill_between(x_inputs, eu_sales + na_sales, na_sales, label="EU Sales")
plt.fill_between(x_inputs, na_sales + eu_sales + jp_sales, na_sales + eu_sales, label="JP Sales")

plt.legend()

<matplotlib.legend.Legend at 0x28a0258ac30>

plt.scatter(vg_sales["Year"],vg_sales["EU_Sales"])

<matplotlib.collections.PathCollection at 0x28a026ffaa0>

	Rank	Name	Platform	Year	Genre	Publisher	NA_Sales	EU_Sales	JP_Sales	Other_Sales	Global_Sales
0	1	Wii Sports	Wii	2006	Sports	Nintendo	41.49	29.02	3.77	8.46	82.74
1	2	Super Mario Bros.	NES	1985	Platform	Nintendo	29.08	3.58	6.81	0.77	40.24
2	3	Mario Kart Wii	Wii	2008	Racing	Nintendo	15.85	12.88	3.79	3.31	35.82
3	4	Wii Sports Resort	Wii	2009	Sports	Nintendo	15.75	11.01	3.28	2.96	33.00
4	5	Pokemon Red/Pokemon Blue	GB	1996	Role-Playing	Nintendo	11.27	8.89	10.22	1.00	31.37
...	...	...	...	...	...	...	...	...	...	...	...
295	296	Far Cry 4	PS4	2014	Shooter	Ubisoft	1.12	2.12	0.10	0.69	4.03
296	297	Star Fox 64	N64	1997	Shooter	Nintendo	2.78	0.58	0.64	0.04	4.03
297	298	Minecraft	PS4	2014	Misc	Sony Computer Entertainment Europe	1.38	1.87	0.12	0.65	4.02
298	299	Golf	NES	1984	Sports	Nintendo	1.22	0.28	2.46	0.04	4.01
299	300	Fallout 3	PS3	2008	Role-Playing	Bethesda Softworks	2.15	1.20	0.07	0.59	4.01

	Rank	Name	Platform	Year	Genre	Publisher	NA_Sales	EU_Sales	JP_Sales	Other_Sales	Global_Sales
4	5	Pokemon Red/Pokemon Blue	GB	1996	Role-Playing	Nintendo	11.27	8.89	10.22	1.00	31.37
5	6	Tetris	GB	1989	Puzzle	Nintendo	23.20	2.26	4.22	0.58	30.26
12	13	Pokemon Gold/Pokemon Silver	GB	1999	Role-Playing	Nintendo	9.00	6.18	7.20	0.71	23.10
21	22	Super Mario Land	GB	1989	Platform	Nintendo	10.83	2.71	4.18	0.42	18.14
30	31	Pokémon Yellow: Special Pikachu Edition	GB	1998	Role-Playing	Nintendo	5.89	5.04	3.12	0.59	14.64
50	51	Super Mario Land 2: 6 Golden Coins	GB	1992	Adventure	Nintendo	6.16	2.04	2.69	0.29	11.18
132	133	Pokémon Crystal Version	GB	2000	Role-Playing	Nintendo	2.55	1.56	1.29	0.99	6.39
170	171	Dr. Mario	GB	1989	Puzzle	Nintendo	2.18	0.96	2.00	0.20	5.34
171	172	Pokemon Pinball	GB	1999	Misc	Nintendo	3.02	1.12	1.01	0.16	5.31
184	185	Super Mario Land 3: Wario Land	GB	1994	Platform	Nintendo	2.49	0.98	1.57	0.15	5.19
191	192	Kirby's Dream Land	GB	1992	Platform	Nintendo	2.71	0.61	1.70	0.11	5.13
200	201	Super Mario Bros.	GB	1999	Platform	Nintendo	3.40	1.30	0.15	0.22	5.07

Bar Chart of Top selling Game Boy Games¶

Frequency of Genre in all GBA games¶

Most popular genres in GB games¶

NA Sales of games through years¶

Sales Compared to Eachother¶

Games Sold in EU¶