目录
Lession 02 : Jupyter Notebooks
Lession 05 : Matplotlib and Seaborn Part 1
Lession 06 : Matplotlib and Seaborn Part 2
Lession 01 : Anaconda
(tea_facts) [wlsh@wlsh-MacbookPro] ~$ conda deactivate
(tea_facts) [wlsh@wlsh-MacbookPro] ~$
(tea_facts) [wlsh@wlsh-MacbookPro] ~$ conda list
WARNING: The conda.compat module is deprecated and will be removed in a future release.
# packages in environment at /usr/local/anaconda3/envs/tea_facts:
#
# Name Version Build Channel
ca-certificates 2019.1.23 0
certifi 2019.3.9 py37_0
libcxx 4.0.1 hcfea43d_1
libcxxabi 4.0.1 hcfea43d_1
libedit 3.1.20181209 hb402a30_0
libffi 3.2.1 h475c297_4
ncurses 6.1 h0a44026_1
openssl 1.1.1b h1de35cc_1
pip 19.1.1 py37_0
python 3.7.3 h359304d_0
readline 7.0 h1de35cc_5
setuptools 41.0.1 py37_0
sqlite 3.28.0 ha441bb4_0
tk 8.6.8 ha441bb4_0
wheel 0.33.2 py37_0
xz 5.2.4 h1de35cc_4
zlib 1.2.11 h1de35cc_3
(tea_facts) [wlsh@wlsh-MacbookPro] ~$ conda install numpy pandas matplotlib
(tea_facts) [wlsh@wlsh-MacbookPro] ~$ conda install jupyter notebook
(tea_facts) [wlsh@wlsh-MacbookPro] ~$ conda list
(base) [wlsh@wlsh-MacbookPro] ~$ conda upgrade conda
(base) [wlsh@wlsh-MacbookPro] ~$ conda upgrade --all
(base) [wlsh@wlsh-MacbookPro] ~$ conda search '*beautifulsoup*'
[wlsh@wlsh-MacbookPro] ~$ conda create -n tea_facts python=3
[wlsh@wlsh-MacbookPro] ~$ source activate tea_facts
(tea_facts) [wlsh@wlsh-MacbookPro] ~$ conda deactivate
(base) [wlsh@wlsh-MacbookPro] ~$ source deactivate
(tea_facts) [wlsh@wlsh-MacbookPro] ~$ conda env export
Lession 02 : Jupyter Notebooks
- Concept 01: Instructor
- Concept 02: What are Jupyter notebooks?
- Concept 03: Installing Jupyter Notebook
- Concept 04: Launching the notebook server
- Concept 05: Notebook interface
- Concept 06: Code cells
- Concept 07: Markdown cells
- Concept 08: Keyboard shortcuts
- Concept 09: Magic keywords
- Concept 10: Converting notebooks
- Concept 11: Creating a slideshow
- Concept 12: Finishing up
Lession 03 : Numpy
- Concept 01: Instructors
- Concept 02: Introduction to NumPy
- Concept 03: Why Use NumPy?
- Concept 04: Creating and Saving NumPy ndarrays
- Concept 05: Using Built-in Functions to Create ndarrays
- Concept 06: Create an ndarray
- Concept 07: Accessing, Deleting, and Inserting Elements Into ndarrays
- Concept 08: Slicing ndarrays
- Concept 09: Boolean Indexing, Set Operations, and Sorting
- Concept 10: Manipulating ndarrays
- Concept 11: Arithmetic operations and Broadcasting
- Concept 12: Creating ndarrays with Broadcasting
- Concept 13: Getting Set Up for the Mini-Project
- Concept 14: Mini-Project: Mean Normalization and Data Separation
Lession 04 : Pandas
- Concept 01: Instructors
- Concept 02: Introduction to Pandas
- Concept 03: Why Use Pandas?
- Concept 04: Creating Pandas Series
- Concept 05: Accessing and Deleting Elements in Pandas Series
- Concept 06: Arithmetic Operations on Pandas Series
- Concept 07: Manipulate a Series
- Concept 08: Creating Pandas DataFrames
- Concept 09: Accessing Elements in Pandas DataFrames
- Concept 10: Dealing with NaN
- Concept 11: Manipulate a DataFrame
- Concept 12: Loading Data into a Pandas DataFrame
- Concept 13: Getting Set Up for the Mini-Project
- Concept 14: Mini-Project: Statistics From Stock Data
Lession 05 : Matplotlib and Seaborn Part 1
- Concept 01: Instructor
- Concept 02: Introduction
- Concept 03: Tidy Data
- Concept 04: Bar Charts
- Concept 05: Absolute vs. Relative Frequency
- Concept 06: Counting Missing Data
- Concept 07: Bar Chart Practice
- Concept 08: Pie Charts
- Concept 09: Histograms
- Concept 10: Histogram Practice
- Concept 11: Figures, Axes, and Subplots
- Concept 12: Choosing a Plot for Discrete Data
- Concept 13: Descriptive Statistics, Outliers and Axis Limits
- Concept 14: Scales and Transformations
- Concept 15: Scales and Transformations Practice
- Concept 16: Lesson Summary
- Concept 17: Extra: Kernel Density Estimation
Lession 06 : Matplotlib and Seaborn Part 2
- Concept 01: Introduction
- Concept 02: Scatterplots and Correlation
- Concept 03: Overplotting, Transparency, and Jitter
- Concept 04: Heat Maps
- Concept 05: Scatterplot Practice
- Concept 06: Violin Plots
- Concept 07: Box Plots
- Concept 08: Violin and Box Plot Practice
- Concept 09: Clustered Bar Charts
- Concept 10: Categorical Plot Practice
- Concept 11: Faceting
- Concept 12: Adaptation of Univariate Plots
- Concept 13: Line Plots
- Concept 14: Additional Plot Practice
- Concept 15: Lesson Summary
- Concept 16: Postscript: Multivariate Visualization
- Concept 17: Extra: Swarm Plots
- Concept 18: Extra: Rug and Strip Plots