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

# # Unsorted and after Sorting Pandas with plot example
# 
# Based on https://stackoverflow.com/questions/44885933/how-to-sort-bars-in-a-bar-plot-in-ascending-order .
# 
# Works in notebooks launched from [here](https://github.com/fomightez/vpython-jupyter).

# In[1]:


#%matplotlib inline
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

#"For examples that use the StringIO class, make sure you import it according to your Python version, i.e. from StringIO import StringIO for Python 2 and from io import StringIO for Python 3." - http://pandas.pydata.org/pandas-docs/stable/io.html
#from StringIO import StringIO # see http://pandas.pydata.org/pandas-docs/stable/io.html
from io import StringIO # see http://pandas.pydata.org/pandas-docs/stable/io.html


input ='''
    Id         Speed
    1          30
    1          35 
    1          31
    2          20
    2          25
    3          80
''' 


# ## First the unsorted example

# In[2]:


df = pd.read_table(StringIO(input), header=0, index_col=None,  delim_whitespace=True)
print(df.head())
result = df.groupby(["Id"])['Speed'].aggregate(np.median).reset_index()

norm = plt.Normalize(df["Speed"].values.min(), df["Speed"].values.max())
#colors = plt.cm.Reds(norm(df["Speed"])) # was causing issues when not at tmpnb.org
# and I didn't want to specify a Seaborn only palette, so just let go to default now

plt.figure(figsize=(12,8))
sns.barplot(x="Id", y="Speed", data=df) # formerly: sns.barplot(x="Id", y="Speed", data=df, palette=colors)
plt.ylabel('Speed', fontsize=12)
plt.xlabel('Id', fontsize=12)
plt.xticks(rotation='vertical')
plt.show()


# ## The Result Sorted by Speed

# In[3]:


result = df.groupby(["Id"])['Speed'].aggregate(np.median).reset_index().sort_values('Speed')
sns.barplot(x='Id', y="Speed", data=df, order=result['Id']) #formerly: sns.barplot(x='Id', y="Speed", data=df, palette=colors, order=result['Id'])
plt.show()


# In[4]:


result


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