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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:
 Matplotlib Exercise 2
Imports
Step1:  Exoplanet properties
Over the past few decades, astronomers have discovered thousands of extrasolar planets. The following paper describes the properties of some of these planets.
http
Step2:  Use np.genfromtxt with a delimiter of ',' to read the data into a NumPy array called data
Step3:  Make a histogram of the distribution of planetary masses. This will reproduce Figure 2 in the original paper.
Customize your plot to follow Tufte's principles of visualizations.
Customize the box, grid, spines and ticks to match the requirements of this data.
Pick the number of bins for the histogram appropriately.
Step4:  Make a scatter plot of the orbital eccentricity (y) versus the semimajor axis. This will reproduce Figure 4 of the original paper. Use a log scale on the x axis.
Customize your plot to follow Tufte's principles of visualizations.
Customize the box, grid, spines and ticks to match the requirements of this data.
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Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
Explanation: Matplotlib Exercise 2
Imports
End of explanation
!head -n 30 open_exoplanet_catalogue.txt
Explanation: Exoplanet properties
Over the past few decades, astronomers have discovered thousands of extrasolar planets. The following paper describes the properties of some of these planets.
http://iopscience.iop.org/1402-4896/2008/T130/014001
Your job is to reproduce Figures 2 and 4 from this paper using an up-to-date dataset of extrasolar planets found on this GitHub repo:
https://github.com/OpenExoplanetCatalogue/open_exoplanet_catalogue
A text version of the dataset has already been put into this directory. The top of the file has documentation about each column of data:
End of explanation
data = np.genfromtxt('open_exoplanet_catalogue.txt' , delimiter = ",")
assert data.shape==(1993,24)
Explanation: Use np.genfromtxt with a delimiter of ',' to read the data into a NumPy array called data:
End of explanation
mass = data[:2]
assert True # leave for grading
Explanation: Make a histogram of the distribution of planetary masses. This will reproduce Figure 2 in the original paper.
Customize your plot to follow Tufte's principles of visualizations.
Customize the box, grid, spines and ticks to match the requirements of this data.
Pick the number of bins for the histogram appropriately.
End of explanation
# YOUR CODE HERE
raise NotImplementedError()
assert True # leave for grading
Explanation: Make a scatter plot of the orbital eccentricity (y) versus the semimajor axis. This will reproduce Figure 4 of the original paper. Use a log scale on the x axis.
Customize your plot to follow Tufte's principles of visualizations.
Customize the box, grid, spines and ticks to match the requirements of this data.
End of explanation
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