# Lesson 22

## Graphics: Other Plots¶

This lesson covers:

• Histograms
• Scatter Plots

Plotting in notebooks requires using a magic command, which starts with %, to initialize the plotting backend.

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# Setup
%matplotlib inline


Begin by loading the data in hf.h5. This data set contains high-frequency price data for IBM and MSFT on a single day stored as two Series. IBM is stored as "IBM" in the HDF file, and MSFT is stored as "MSFT.

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### Problem: Histogram¶

Produce a histogram of MSFT 1-minute returns (Hint: you have to produce the 1-minute Microsoft returns first using resample and pct_change).

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### Problem: Scatter Plot¶

Scatter the 5-minute MSFT returns against the 5-minute IBM returns.

Hint: You will need to create both 5-minute return series, merge them, and then plot using the combined DataFrame.

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### Problem: Saving plots¶

Save the previous plot to PNG and PDF.

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### Exercises¶

#### Exercise: Visualize 5 and 10 minute returns¶

Produce a 2 by 1 subplot with a histogram of the 5-minute returns of IBM in the top panel and 10-minute returns of IBM in the bottom. Set an appropriate title on each of the 2 plots.

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#### Exercise: Export the result of the previous exercise to JPEG and PDF¶

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### Exercise: Plot histograms and a scatter plot¶

Produce a 2 by 2 subplot with:

• Create a square figure with a size of 10 by 10 using plt.rc
• Histograms of IBM and MSFT on the diagonals
• Scatter plots on the off-diagonals where the x and y line up with the histogram on the diagonal.
• Set the limits of the scatter plots to match the appropriate histogram x and y limit.
• Clean up the plot using tight_layout
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#### Exercise: Use pandas plotting tools¶

Use pandas.plotting.scatter_matrix to produce a similar plot to the previous exercise.

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