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

# In[1]:


import numpy as np
import matplotlib.pyplot as plt
from pylab import *
import pandas as pd

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

pSiteFile = 'pSite_growth.csv'
#PhosphoSite/PhosphoSitePlus human tyrosine phosphorylation sites
df = pd.DataFrame.from_csv(pSiteFile)






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nrows = 3
ncols = 2
fig, axes = plt.subplots(nrows=nrows, ncols=ncols)
fig.tight_layout()
fig.autofmt_xdate()
idxCol = 0
idxRow = 0
keys = ('Phosphoserine', 'Phosphothreonine', 'Phosphotyrosine','N6-acetyllysine', 'Ubiquitination', 'Sumoylation')
for key in keys:
    keySubset = df[df['Modification']==key]
    axes[idxRow, idxCol].bar(keySubset['Year'], keySubset['Number'])
    axes[idxRow,idxCol].set_title(key)
    #axes[idxRow,idxCol].get_xaxis().get_major_formatter().set_useOffset(False)
    axes[idxRow,idxCol].get_xaxis().get_major_formatter().set_scientific(False)
    # Tell matplotlib to interpret the x-axis values as dates
    #axes[idxRow,idxCol].xaxis_date()
    idxCol = idxCol + 1
    if idxCol % (nrows-1) == 0:
        idxCol = 0
        idxRow += 1


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