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

# In[1]:


get_ipython().run_line_magic('matplotlib', 'inline')


# In[2]:


from matplotlib import pyplot as plt


# In[3]:


# availables styles
plt.style.available


# In[4]:


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


# In[5]:


# Median Developer Salaries by Age
ages_x = [25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35]

dev_y = [38496, 42000, 46752, 49320, 53200,
         56000, 62316, 64928, 67317, 68748, 73752]

# Median Python Developer Salaries by Age

py_dev_y = [45372, 48876, 53850, 57287, 63016,
            65998, 70003, 70000, 71496, 75370, 83640]

# Median JavaScript Developer Salaries by Age
js_dev_y = [37810, 43515, 46823, 49293, 53437,
            56373, 62375, 66674, 68745, 68746, 74583]


# In[6]:


plt.plot(ages_x, dev_y, label='All Devs')
plt.plot(ages_x, py_dev_y, label='Python')

plt.xlabel("Ages")
plt.ylabel("Median Salary (USD)")
plt.title("Median Salary (USD) by Age")

# adding legend
# method 1
# plt.legend(['All Devs', 'Python'])
# method 2 - pass a label argument to plot

plt.legend()


# * Format Strings
# 
# A format string consists of a part for color, marker and line:
# ```python
# fmt = '[marker][line][color]'
# ```
# 
# 
# **Markers**
# 
# |character|	description|
# |--|--|
# |**.**|	point marker|
# |**,**|	pixel marker|
# |**o**|	circle marker|
# |**v**|	triangle_down marker|
# |**^**|	triangle_up marker|
# |**<**|	triangle_left marker|
# |**>**|	triangle_right marker|
# |**1**|	tri_down marker|
# |**2**|	tri_up marker|
# |**3**|	tri_left marker|
# |**4**|	tri_right marker|
# |**s**|	square marker|
# |**p**|	pentagon marker|
# |*****|	star marker|
# |**h**|	hexagon1 marker|
# |**H**|	hexagon2 marker|
# |**+**|	plus marker|
# |**x**|	x marker|
# |**D**|	diamond marker|
# |**d**|	thin_diamond marker|
# |**'**|	vline marker|
# |**_**|	hline marker|
# 
# 
# **Line Styles**
# 
# |character|	description|
# |--|--|
# |**-**| solid line style|
# |**--**	|dashed line style|
# | **-.**|dash-dot line style|
# | **:**	|dotted line style|
# 
# |Example| format strings:|
# |--|--|
# |**b**|   blue markers with default shape|
# |**or**|   red circles|
# |**-g**|   green solid line|
# |**--**|   dashed line with default color|
# |**^k:**|  black triangle_up markers connected by a dotted line|
# 
# 
# **Colors**
# 
# The supported color abbreviations are the single letter codes
# 
# 
# |character	|color|
# |--|--|
# |**b**|	blue|
# |**g**| green|
# |**r**| red|
# |**c**|	cyan|
# |**m**|	magenta|
# |**y**|	yellow|
# |**k**|	black|
# |**w**|	white|

# In[7]:


# change formatting of the plot
# method 1

plt.plot(ages_x, dev_y, 'k--', label='All Devs')
plt.plot(ages_x, py_dev_y, 'b', label='Python')


plt.xlabel("Ages")
plt.ylabel("Median Salary (USD)")
plt.title("Median Salary (USD) by Age")
plt.legend()


# In[8]:


# proper method / more desirable

plt.plot(ages_x, dev_y, color='k', linestyle='--', marker='.', label='All Devs')
plt.plot(ages_x, py_dev_y, color='b', marker='o', label='Python')
plt.xlabel("Ages")
plt.ylabel("Median Salary (USD)")
plt.title("Median Salary (USD) by Age")
plt.legend()


# In[9]:


# using hexadecimal value for colors and linewidth

plt.plot(ages_x, py_dev_y, linewidth=3, label='Python')

plt.plot(ages_x, js_dev_y, linewidth=3, label='JavaScript')

plt.plot(ages_x, dev_y, color='#444444', linestyle='--', label='All Devs')

plt.xlabel("Ages")
plt.ylabel("Median Salary (USD)")
plt.title("Median Salary (USD) by Age")
plt.legend()

# adding a grid
plt.grid(True)

# Automatically adjust subplot parameters to give specified padding.
plt.tight_layout()
plt.show()


# In[10]:


# using xkcd format

plt.xkcd()
plt.plot(ages_x, py_dev_y, linewidth=3, label='Python')
plt.plot(ages_x, js_dev_y, linewidth=3, label='JavaScript')
plt.plot(ages_x, dev_y, color='#444444', linestyle='--', label='All Devs')
plt.xlabel("Ages")
plt.ylabel("Median Salary (USD)")
plt.title("Median Salary (USD) by Age")
plt.legend()
plt.grid(True)
plt.tight_layout()
# saving file
plt.savefig(r'plots/plot1-1.png')


# In[11]:


# ages 18-55

# Ages 18 to 55
ages_x = [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]

py_dev_y = [20046, 17100, 20000, 24744, 30500, 37732, 41247, 45372, 48876, 53850, 57287, 63016, 65998, 70003, 70000, 71496, 75370, 83640, 84666,
            84392, 78254, 85000, 87038, 91991, 100000, 94796, 97962, 93302, 99240, 102736, 112285, 100771, 104708, 108423, 101407, 112542, 122870, 120000]

js_dev_y = [16446, 16791, 18942, 21780, 25704, 29000, 34372, 37810, 43515, 46823, 49293, 53437, 56373, 62375, 66674, 68745, 68746, 74583, 79000,
            78508, 79996, 80403, 83820, 88833, 91660, 87892, 96243, 90000, 99313, 91660, 102264, 100000, 100000, 91660, 99240, 108000, 105000, 104000]

dev_y = [17784, 16500, 18012, 20628, 25206, 30252, 34368, 38496, 42000, 46752, 49320, 53200, 56000, 62316, 64928, 67317, 68748, 73752, 77232,
         78000, 78508, 79536, 82488, 88935, 90000, 90056, 95000, 90000, 91633, 91660, 98150, 98964, 100000, 98988, 100000, 108923, 105000, 103117]


# In[12]:


plt.plot(ages_x, py_dev_y, linewidth=3, label='Python')
plt.plot(ages_x, js_dev_y, linewidth=3, label='JavaScript')
plt.plot(ages_x, dev_y, color='#444444', linestyle='--', label='All Devs')
plt.xlabel("Ages")
plt.ylabel("Median Salary (USD)")
plt.title("Median Salary (USD) by Age")
plt.legend()
plt.grid(True)
plt.tight_layout()
plt.savefig(r'plots/plot1-2.png')