#!/usr/bin/env python
# coding: utf-8

# # Loading Necessary Libraries

# In[2]:


import matplotlib.pyplot as plt
import numpy as np
from numpy.random import randint
import pandas as pd
get_ipython().run_line_magic('matplotlib', 'inline')


# # Data Visualization

# ### Types of Graphs covered:

# - **Line Graph**
#     - **Basics**
#     - **Subplots**
# - **Bar Chart**
# - **Pie Chart**
# - **Box & Whiskers Plot**

# # Line Graph (Basics)

# In[5]:


x = [1, 2, 3, 8, 9, 23]
y = [5, 13, 10, 11, 45, 27]

plt.style.use('dark_background')

plt.rcParams['figure.figsize'] = (10,4)

#Line 1

#Keyword Argument Notation
#plt.plot(x,y, label='2x', color='red', linewidth=2, marker='.', linestyle='--', markersize=10, markeredgecolor='blue')

#Sorthand Notation
#format = '[color][marker][line]'

plt.plot(x,y, 'g^--', label = 'A simple line', linewidth = 2)

#Line 2

# select interval we want to plot points at
x2 = np.arange(0,8.5,0.5)

# Plot part of the graph as line
plt.plot(x2[:10], x2[:10]**2, 'r', label = 'X^2') 
plt.plot(x2[9:], x2[9:]**2,  'r--')

#add title to graph
plt.title('Line Graph', loc = 'left', fontdict = {'fontname': 'Times New Roman', 'color': 'white', 'fontsize' : '22'})

#add title to axis
plt.xlabel('X-axis', fontdict = {'color': 'white', 'fontsize' : '16'})
plt.ylabel('Y-axis', fontdict = {'color': 'white', 'fontsize' : '16'})

#Ticks are the markers denoting data points on axes.
#plt.xticks([0,2,4,6,8,10,12,14,16,18,20,22,24])
#plt.yticks([5,10,15,20,25,30,35,40,45])
         
#add legend
plt.legend(loc = 0)

#save graph
plt.savefig('mygraph.png', dpi = 200)

#show graph
plt.show()


# # Multiple Plots in the same Canvas : Subplots

# ## Two Plots Together

# In[141]:


x = np.linspace(0,10,20)
x


# In[142]:


y = randint(1, 50, 20)
y


# In[6]:


x = np.linspace(0,10,20)
y = randint(1, 50, 20)

plt.style.use('dark_background')

plt.rcParams['figure.figsize'] = (10,4)

# Plot 1
plt.subplot(1,2,1)
plt.plot(x, y, 'c:o')
plt.title('A Cyan Plot', fontdict = {'fontname': 'Times New Roman', 'color' : 'cyan'})
#Plot 2
plt.subplot(1,2,2)
plt.plot(x, y, 'r--_')
plt.title('A Red Plot', fontdict = {'fontname': 'Times New Roman', 'color' : 'red'})

#Title at Top
plt.suptitle('Two Plots Together', fontdict = {'fontname': 'Times New Roman', 'color': 'white'})

plt.show()


# ## Three Plots Together

# In[17]:


x = np.linspace(0,10,20)
y = randint(1, 50, 20)

plt.style.use('dark_background')

plt.rcParams['figure.figsize'] = (12,4)

# Plot 1
plt.subplot(1,3,1)
plt.plot(x, y, 'c:o')
plt.title('A Cyan Plot', fontdict = {'fontname': 'fantasy', 'color' : 'cyan'})

#Plot 2
plt.subplot(1,3,2)
plt.plot(x, y**y, 'r--_')
plt.title('A Red Plot', fontdict = {'fontname': 'fantasy', 'color' : 'red'})

#Plot 3
plt.subplot(1,3,3)
plt.plot(x, y*x, 'g-^')
plt.title('A Green Plot', fontdict = {'fontname': 'fantasy', 'color' : 'green'})

#Labeling
plt.suptitle('Three Plots Together', fontdict = {'fontname': 'fantasy', 'color': 'white'})

plt.savefig('threeplots.png')

plt.show()


# ## Different Methods of Creating Subplots

# ### Object Oriented Method

# In[199]:


fig = plt.figure(figsize= (10,4))

ax1 = fig.add_axes([0,0,1,1])
ax2 = fig .add_axes([0.1, 0.1, 0.4, 0.3])

ax1.plot(x, y)
ax2.plot(x, y*2)

plt.show()


# ### Brute Force Method to plot more than one graphs

# In[200]:


fig, ax = plt.subplots(1,2, figsize= (10,4))

ax[0].plot(x, y, 'b')
ax[1].plot(x, y*x, 'r-.')

plt.show()


# ### For Loop Method

# In[201]:


fig , ax = plt.subplots(1,2, figsize= (10,4))

col = ['g', 'm']
data = [y, y**y]

for i, axes in enumerate(ax):
    axes.plot(x, data[i], col[i])

fig.tight_layout()


# ## **Setting X and Y limits of subplots**

# In[162]:


fig, ax = plt.subplots(1,3, figsize = (12, 4))

#Get three plots simultaneously
ax[0].plot(x, y, x, y*x)

ax[1].plot(x, y**2, 'r')
#setting limits to y axis
ax[1].set_ylim([0,1000])

ax[2].plot(x, y, x, y*x)
#setting limits to x and y axes
ax[2].set_ylim([0,300])
ax[2].set_xlim([0,5])

plt.show()


# ## **Plotting Log(x) on a subplot**

# In[180]:


fig, ax = plt.subplots(1,2, figsize = (10,4))

ax[0].plot(x, y, x, y**2)

ax[1].plot(x, np.exp(x), 'w')
#plotting log of x
ax[1].set_yscale('log')

plt.show()


# ## Setting Xticks and Yticks and Changing their Labels

# In[193]:


fig, ax = plt.subplots(figsize = (10,4))

ax.plot(x, y)

ax.set_xticks([1,2,5,10])
ax.set_xticklabels([r'a', r'B', r'$\alpha$', r'$\delta$'], fontsize = 20)

ax.set_yticks([1,15,25,50])

plt.show()


# ## Setting Y-axis Label as Scientific Notation

# In[196]:


from matplotlib import ticker


# In[198]:


fig, ax = plt.subplots(figsize = (10,4))
ax.plot(x, y)
ax.set_title('Scientific Notation')

formatter = ticker.ScalarFormatter(useMathText = True)

formatter.set_scientific(True)
formatter.set_powerlimits((-1,-1))
ax.yaxis.set_major_formatter(formatter)

plt.show()


# # Bar Chart (Basics)

# In[8]:


labels = ['A', 'B', 'C']
values = [6, 8, 3]

plt.style.use('dark_background')

plt.rcParams['figure.figsize'] = (10,4)

bars = plt.bar(labels, values, align = 'edge', edgecolor = 'indigo', facecolor = 'pink')

#adding title
plt.title('Bar Graph', loc = 'right', fontdict = {'fontname': 'Times New Roman', 'color': 'white', 'fontsize': '30'})

#adding label to axis 
plt.xlabel('X-axis', fontdict = {'color': 'white','fontsize' : '16'})
plt.ylabel('Y-axis', fontdict = {'color': 'white','fontsize' : '16'})
 

#add patterns to bars
bars[0].set_hatch('O')
bars[1].set_hatch('*')
bars[2].set_hatch('+')


plt.show()


# # Real World Examples

# ## Line Chart 

# - **Data selected for analysis**

# In[6]:


gas = pd.read_csv('gas_prices.csv')

gas


# - **Line Chart showing changes in the prices of gas (USD/gallon)**

# In[7]:


#add title to graph
plt.title('Change in Gas Prices', loc = 'center', fontdict = {'fontname': 'century','color': 'white', 'fontsize': '25'})

#changing style of the graph
plt.style.use('dark_background')

#add title to axislightblue
plt.xlabel('Change over Years', fontdict = {'fontname': 'century', 'color': 'white','fontsize' : '17'})
plt.ylabel('Prices (USD/Gallon)', fontdict = {'fontname': 'century', 'color': 'white','fontsize' : '17'})

#plotting all countries in the graph 
for country in gas:
    if country != 'Year':
        plt.plot(gas.Year, gas[country], marker = '.') 

plt.xticks(gas.Year[::2])
#[::2] allows to have two years ga in the xticks

#adding legend
plt.legend(['Australia', 'Canada', 'France', 'Germany', 'Italy', 'Japan', 'Mexico', 'South Korea', 'UK', 'USA'], loc = 0, bbox_to_anchor=(1,1))
#bbox_to_anchor=(1,1) puts the legend outside the graph

plt.savefig('gas_prices.png', dpi= 300, bbox_inches='tight')
#bbox_inches='tight' prevents the graph from getting cropped

plt.show()


# - **Line Chart showing changes in the prices of gas (USD/gallon) in USA, Italy , France and Germany only**

# In[8]:


#add title to graph
plt.title('Change in Gas Prices', loc = 'center', fontdict = {'fontname': 'century', 'color': 'white', 'fontsize': '25'})

#changing style of the graph
plt.style.use('dark_background')

#add title to axis
plt.xlabel('Change over Years', fontdict = {'fontname': 'century', 'color': 'white','fontsize' : '17'})
plt.ylabel('Prices (USD/Gallon)', fontdict = {'fontname': 'century', 'color': 'white','fontsize' : '17'})

#Method 1

# plt.plot(gas.Year, gas.USA, 'b.--')
# plt.plot(gas.Year, gas.Canada, 'r.-')
# plt.plot(gas.Year, gas.France, 'y.:')
# plt.plot(gas.Year, gas.Germany, 'g.:')

#Method 2

specific_countries = ['USA', 'France', 'Germany', 'Italy']

for country in gas:
    plt.plot(gas.Year, gas[specific_countries], marker = '.') 

#adding blank year in the graph and customizing xticks
plt.xticks(gas.Year[::2].tolist()+[2010])

#adding legend
plt.legend(['USA', 'France', 'Germany', 'Italy'], loc = 0, bbox_to_anchor=(1,1))

plt.savefig('gas_prices_specific.png', dpi= 300, facecolor = 'white', bbox_inches='tight')

plt.show()


# # Histogram

# - **Data selected for Analysis**

# In[10]:


fifa = pd.read_csv('fifa_data.csv')

fifa.head()


# - **Distribution of Players Overall Skills in FIFA 2018**

# In[11]:


bins = [70,80,90,100]

#add title to graph
plt.title('Distribution of Players Overall Skills', loc = 'center', fontdict = {'fontname': 'century', 'color': 'white', 'fontsize': '22'})

#add title to axis
plt.xlabel('Overall Skill Points', fontdict = {'fontname': 'century', 'color': 'white','fontsize' : '15'})
plt.ylabel('Number of Players', fontdict = {'fontname': 'century', 'color': 'white','fontsize' : '15'})

plt.style.use('dark_background')

plt.rcParams['figure.figsize'] = (10,4)

plt.hist(fifa.Overall, bins = bins, color = 'cyan')

plt.show()


# # Pie Chart

# - **Preferred Foot by FIFA Players**

# In[13]:


fifa['Preferred Foot']


# In[12]:


left = fifa.loc[fifa['Preferred Foot'] == 'Left'].count()[0]
right = fifa.loc[fifa['Preferred Foot'] == 'Right'].count()[0]

labels = [right, left]

plt.pie(labels, labeldistance = 1.3, labels = labels, colors = ['crimson', 'lightcoral'], autopct= '%.2f %%')

plt.title('Preferred Foot by FIFA Players', loc = 'center', fontdict = {'fontname': 'century', 'color': 'white', 'fontsize': '20'})

plt.style.use('dark_background')

plt.rcParams['figure.figsize'] = (10,4)

plt.show()


# - **Weight Distribution of FIFA Players**

# In[275]:


fifa.Weight


# In[14]:


fifa.Weight = [
    int(x.strip('lbs')) 
    if type(x) == str
    else 
    x for x in fifa.Weight
]

fifa.Weight


# In[15]:


plt.style.use('seaborn-ticks')

light = fifa.loc[fifa.Weight < 125].count()[0]
light_medium = fifa[(fifa.Weight >= 125) & (fifa.Weight < 150)].count()[0]
medium = fifa[(fifa.Weight >= 150) & (fifa.Weight < 175)].count()[0]
medium_heavy = fifa[(fifa.Weight >= 175) & (fifa.Weight < 200)].count()[0]
heavy = fifa[fifa.Weight >= 200].count()[0]

weights = [light,light_medium, medium, medium_heavy, heavy]
label = ['under 125', '125-150', '150-175', '175-200', 'over 200']
explode = (.3,.2,0,0,.3)

plt.title('Weight of Professional Soccer Players (lbs)',  loc = 'center', fontdict = {'fontname': 'century', 'color': 'navy', 'fontsize': '20'})

plt.pie(weights, labeldistance = 1.3, wedgeprops = {'linewidth': 5}, labels=label, explode=explode, pctdistance=0.9, autopct='%.2f %%')

plt.rcParams['figure.figsize'] = (10,4)

plt.show()


# # Box and Whiskers Chart

# - **Comparing FIFA teams with one another**

# In[18]:


plt.style.use('dark_background')
plt.figure(figsize = (6,8))

barcelona = fifa.loc[fifa.Club == 'FC Barcelona']['Overall']
madrid = fifa.loc[fifa.Club == 'Real Madrid']['Overall']
juventus = fifa.loc[fifa.Club == 'Juventus']['Overall']
manchester = fifa.loc[fifa.Club == 'Manchester United']['Overall']

plt.title('FIFA Football Teams Comparison',  loc = 'center', fontdict = {'fontname': 'century', 'color': 'white', 'fontsize': '20'})

plt.boxplot([barcelona, madrid, juventus, manchester], labels = ['FC Barcelona', 'Real Madrid', 'Juventus', 'Manchester United'])

plt.show()