Understand Python libraries (matplotlib, numpy, and pandas) and their functionalities. Learn basic methods and attributes to create simple graphs (line graph, bar chart, histogram, and pie chart)

1. Data Visualization
with Python
Nhi Nguyen

2. Pre-Workshop Checklist
⬡ This is pretty obvious…. but do you have your laptop with you? If
you don’t…. Perhaps go grab it?
⬡ Did you download Anaconda?
⬡ Did you have access to TD WS 1 Shared Folder? (on AIS website)
⬡ If you encounter issues → ask our Student Assistants!
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3. “ ● Speaker Series 2 : Abha Kumar
○ 02/17 from 12-1pm
● Phillies Office Visit
○ 02/27 (9:00-12:30)
○ Signups in the Newsletter
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AIS Upcoming Events

4. “
4
Technical Development
Track Requirements
3
Friday
meetings
2
Saturday
workshops

5. Hello from our volunteers!
Justin
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Jianjin Luke

6. TODAY’S AGENDA
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PART 1
LINE CHART
DIY EXERCISES
PART 3
BAR CHART
DIY EXERCISES
OVERVIEW
GENERAL CONCEPT
SETTING UP
PART 2
PIE CHART
DIY EXERCISES
PART 4
HISTOGRAM
DIY EXERCISES
REVIEW
RESOURCES
SUBMISSION & FEEDBACK

7. OVERVIEW
General Concept | Setting Up

8. Python libraries
▸ pd as alias
▸ data structures and
operations
▸ data manipulation and
analysis
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▸ np as alias
▸ multi-dimensional arrays
and matrices
▸ high-level mathematical
functions
▸ plt as alias
▸ plotting library
▸ Object-oriented API

9. Python libraries
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MATLAB-style
Syntax
Object-oriented
Syntax
▸ Scripted
▸ Structured
▸ Beginner
▸ More control
▸ Personalization
Hybrid

10. LET’S GET YOU SET UP!

11. PART 1
Simple Line Graph | Multiple Lines
DIY Exercise

12. Line Graph
Used to track changes over short and long
periods of time.
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13. Some methods and attributes
plot()
Take arrays and turn them to
line graphs
show()
Used to invoke the required plot
title()
Create title for graphs
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xlabel() and ylabel()
Create x label and y label
fontsize
Adjust the size for the titles,
xlabel, ylabel, etc.
color or c
Change color

14. Some methods and attributes
linestyle or ls
Provide a variety of styles for
lines
figure()
Manipulate and adjust things to
the figure
figsize
Change the size of your figure
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savefig()
Save graphs to your folder
legend()
Create legend for graphs

15. DIY Exercise
Line Graph
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16. PART 2
Pie Chart | DIY Exercise

17. Pie Chart
Used to tell a story about the parts-to-whole
aspect of a set of data (usually percentage).
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18. Some methods and attributes
pie()
Create pie charts
startangle
Adjust slides’ positions
explode
Cut slides
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19. DIY Exercise
Pie Chart
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20. PART 3
Bar Chart | Horizontal Bar
Multiple Bars | DIY Exercise

21. Bar Chart
Used to compare differences between groups/categories.
Also used to track changes over time
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22. Load & Understand Dataset
read_excel()
Import excel files to Jupyter
Notebook
dtypes
Check the data types in each
column of a dataset
shape
Provide number of rows and
columns in a dataset
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head() and tail()
Load first 5 rows
Load last 5 rows
info
Identity data types and null values
color or c
Change color

23. Rename columns
& Convert df to numpy arrays
rename()
Rename one column
columns
Rename multiple columns
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loc
Load each column’s values
values
Convert pandas df to numpy arrays

24. Some methods and attributes
bar()
Create vertical bar graphs
barh()
Create horizontal bar graphs
xticks() and yticks()
Provide reference for points on a
scale for x and y axes
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np.arange()
Create a numpy array

25. DIY Exercise
Bar Chart
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26. PART 4
Histogram | DIY Exercise

27. Histogram
Help you discover, and show, the underlying
frequency distribution of a dataset
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28. Some methods and attributes
hist()
Create histograms
np.random.randn()
Create random numbers
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29. DIY Exercise
Histogram
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30. Additional
learning resources
▸ Online Course: Data
Visualization for Python
▸ Matplotlib main website
▸ Real Python tutorials
▸ Free data sets
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31. MAKE SURE YOU HAVE ALL
YOUR GRAPHS IN THE WORD
DOC TO SUBMIT FOR
PARTICIPATION!

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Thanks for coming!
Suitable Code AIS Attendance
http://bit.ly/SAT-TD1
Exit Code: water