I need help with python 3.x, I dont know how to to do this question. Can anyone

Question

I need help with python 3.x, I dont know how to to do this question. Can anyone help me please. The code has to be in python 3.x. Thanks!

12. matplotlib is a powerful graphing package for Python that can draw histograms, bar charts, scatter plots, and many other kinds of graphs. It is particularly useful if you are taking any science course analyze data. You can read about and download matplotlib for your computer at http://matplotlib.sourceforge.net/. Read the documentation to learn how to use this module to plot a histogram of the data generated by the following code: def randomList_gauss ): where you may need to graph and random1st = [] mu = .4 sigma = .2 for i in range (1000): rand = float ("%"If" % gauss(mu, randomList.append (rand) sigma)) return randomList Add graphical representations of the mean and the standard deviation to the his- togram.

Explanation / Answer

# Standard import for pandas, numpy and matplot
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

# Read in the csv file and display some of the basic info
sales=pd.read_csv("sample-salesv2.csv",parse_dates=['date'])
print "Data types in the file:"
print sales.dtypes
print "Summary of the input file:"
print sales.describe()
print "Basic unit price stats:"
print sales['unit price'].describe()

# Filter the columns down to the ones we need to look at for customer sales
customers = sales[['name','ext price','date']]

#Group the customers by name and sum their sales
customer_group = customers.groupby('name')
sales_totals = customer_group.sum()

# Create a basic bar chart for the sales data and show it
bar_plot = sales_totals.sort(columns='ext price',ascending=False).plot(kind='bar',legend=None,title="Total Sales by Customer")
bar_plot.set_xlabel("Customers")
bar_plot.set_ylabel("Sales ($)")
plt.show()

# Do a similar chart but break down by category in stacked bars
# Select the appropriate columns and group by name and category
customers = sales[['name','category','ext price','date']]
category_group = customers.groupby(['name','category']).sum()

# Plot and show the stacked bar chart
stack_bar_plot = category_group.unstack().plot(kind='bar',stacked=True,title="Total Sales by Customer",figsize=(9, 7))
stack_bar_plot.set_xlabel("Customers")
stack_bar_plot.set_ylabel("Sales")
stack_bar_plot.legend(["Total","Belts","Shirts","Shoes"], loc=9,ncol=4)
plt.show()

# Create a simple histogram of purchase volumes
purchase_patterns = sales[['ext price','date']]
purchase_plot = purchase_patterns['ext price'].hist(bins=20)
purchase_plot.set_title("Purchase Patterns")
purchase_plot.set_xlabel("Order Amount($)")
purchase_plot.set_ylabel("Number of orders")
plt.show()

# Create a line chart showing purchases by month
purchase_patterns = purchase_patterns.set_index('date')
month_plot = purchase_patterns.resample('M',how=sum).plot(title="Total Sales by Month",legend=None)
fig = month_plot.get_figure()

#Show the image, then save it
plt.show()
fig.savefig("total-sales.png")

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