Image 1 of 1: ‘Anaconda Navigator landing page’
Anaconda Navigator landing page
Image 1 of 1: ‘Anaconda Navigator landing page’
Anaconda Navigator landing page
Image 1 of 1: ‘JupyterLab Menu Bar’
JupyterLab Menu Bar
Image 1 of 1: ‘JupyterLab Left Side Bar’
JupyterLab Left Side Bar
Image 1 of 1: ‘JupyterLab Main Work Area’
JupyterLab Main Work Area
Image 1 of 1: ‘Example Jupyter Notebook’
Example Jupyter Notebook
Image 1 of 1: ‘Multi-panel JupyterLab’
Multi-panel JupyterLab
Image 1 of 1: ‘Python uses 0-based indexing.’
Python uses 0-based indexing.
Image 1 of 1: ‘veg is represented as a shelf full of produce. There are three rows of vegetables on the shelf, and each row contains three baskets of vegetables. We can label each basket according to the type of vegetable it contains, so the top row contains (from left to right) lettuce, lettuce, and peppers.’
veg
is represented as a shelf full
of produce. There are three rows of vegetables on the shelf, and each
row contains three baskets of vegetables. We can label each basket
according to the type of vegetable it contains, so the top row contains
(from left to right) lettuce, lettuce, and peppers.
Image 1 of 1: ‘veg is now shown as a list of three rows, with veg[0] representing the top row of three baskets, veg[1] representing the second row, and veg[2] representing the bottom row.’
veg
is now shown as a list of three
rows, with veg[0]
representing the top row of three
baskets, veg[1]
representing the second row, and
veg[2]
representing the bottom row.
Image 1 of 1: ‘veg is now shown as a two-dimensional grid, with each basket labeled according to its index in the nested list. The first index is the row number and the second index is the basket number, so veg[1][3] represents the basket on the far right side of the second row (basket 4 on row 2): zucchini’
To reference a specific basket on a specific shelf, you use two
indexes. The first index represents the row (from top to bottom) and the
second index represents the specific basket (from left to right).
Image 1 of 1: ‘Changing the kernel’
Changing the kernel
Image 1 of 1: ‘Selecting conda kernels in Jupyer Lab’
Selecting conda kernels in Jupyer Lab
Image 1 of 1: ‘Illustrative diagram of associative arrays, showing the sets of keys and their association with some of the values.’
Illustrative diagram of associative arrays,
showing the sets of keys and their association with some of the
values.
Image 1 of 1: ‘Melt goes from wide to long data’
Melt goes from wide to long data
Image 1 of 1: ‘Pivot_table goes from long to wide’
Pivot_table goes from long to wide
Image 1 of 1: ‘A summary of the types of joins and what they keep and drop.’
A summary of the types of joins and what they
keep and drop.
Image 1 of 1: ‘Simple Position-Time Plot’
Simple Position-Time Plot
Image 1 of 1: ‘Expression histogram’
Expression histogram
Image 1 of 1: ‘Boxplot by timepoint’
Boxplot by timepoint
Image 1 of 1: ‘Histogram by timpoint as subplots.’
Histogram by timpoint as subplots.
Image 1 of 1: ‘Asl expression over time’
Asl expression over time
Image 1 of 1: ‘Multiple lines on the same plot with a legend’
Multiple lines on the same plot with a
legend
Image 1 of 1: ‘A simple boxplot using seaborn’
A simple boxplot using seaborn
Image 1 of 1: ‘Basic foldchange scatterplot.’
Basic foldchange scatterplot.
Image 1 of 1: ‘Axis labels changed’
Axis labels changed
Image 1 of 1: ‘Adjusted alpha level’
Adjusted alpha level
Image 1 of 1: ‘Adjusted point size’
Adjusted point size
Image 1 of 1: ‘Added gene_biotype as hue’
Added gene_biotype as hue
Image 1 of 1: ‘Style set to is_protein_coding’
Style set to is_protein_coding
Image 1 of 1: ‘Adding chromosome’
Adding chromosome
Image 1 of 1: ‘Cleaning up the plot’
Cleaning up the plot
Image 1 of 1: ‘Default clustered heatmap’
Default clustered heatmap
Image 1 of 1: ‘Using magma colormap’
Using magma colormap
Image 1 of 1: ‘Heatmap with infection information’
Heatmap with infection information
Image 1 of 1: ‘Supervised Machine Learning Workflow’
Supervised Machine Learning Workflow
Image 1 of 1: ‘Splitting a training set’
.
Image 1 of 1: ‘Holdout validation strategy’
Holdout validation strategy
Image 1 of 1: ‘ROC curve’
ROC curve
Image 1 of 1: ‘PR curve’
PR curve
Image 1 of 1: ‘Confusion Matrix’
Confusion Matrix