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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Title
Step1:  Create dataframe
Step2:  Make plot
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Python Code:
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
Explanation: Title: Back To Back Bar Plot In MatPlotLib
Slug: matplotlib_back_to_back_bar_plot
Summary: Back To Back Bar Plot In MatPlotLib
Date: 2016-05-01 12:00
Category: Python
Tags: Data Visualization
Authors: Chris Albon  
Based on: Sebastian Raschka.
Preliminaries
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raw_data = {'first_name': ['Jason', 'Molly', 'Tina', 'Jake', 'Amy'],
        'pre_score': [4, 24, 31, 2, 3],
        'mid_score': [25, 94, 57, 62, 70],
        'post_score': [5, 43, 23, 23, 51]}
df = pd.DataFrame(raw_data, columns = ['first_name', 'pre_score', 'mid_score', 'post_score'])
df
Explanation: Create dataframe
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# input data, specifically the second and 
# third rows, skipping the first column
x1 = df.ix[1, 1:]
x2 = df.ix[2, 1:]
# Create the bar labels
bar_labels = ['Pre Score', 'Mid Score', 'Post Score']
# Create a figure
fig = plt.figure(figsize=(8,6))
# Set the y position
y_pos = np.arange(len(x1))
y_pos = [x for x in y_pos]
plt.yticks(y_pos, bar_labels, fontsize=10)
# Create a horizontal bar in the position y_pos
plt.barh(y_pos, 
         # using x1 data
         x1, 
         # that is centered
         align='center', 
         # with alpha 0.4
         alpha=0.4, 
         # and color green
         color='#263F13')
# Create a horizontal bar in the position y_pos
plt.barh(y_pos, 
         # using NEGATIVE x2 data
         -x2,
         # that is centered
         align='center', 
         # with alpha 0.4
         alpha=0.4, 
         # and color green
         color='#77A61D')
# annotation and labels
plt.xlabel('Tina\'s Score: Light Green. Molly\'s Score: Dark Green')
t = plt.title('Comparison of Molly and Tina\'s Score')
plt.ylim([-1,len(x1)+0.1])
plt.xlim([-max(x2)-10, max(x1)+10])
plt.grid()
plt.show()
Explanation: Make plot
End of explanation
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