This cheat sheet provides a quick look into the essential functions like reading the data, selecting sorting, etc. On top of this, it also includes basic data queries like joins, merges, etc. The Pandas machine learning cheat sheet can be accessed here. Matplotlib cheat sheet by Justin. Matplotlib can quickly draw complex graphs and diagrams. - %% ## ↵ ↵ ↵ ↵ ↵. Cheatsheet - Matplotlib Charts This kernel is all about matplotlib charts - the basic python data visualization tool. Please Upvote my kernel and keep it in your favourite section if you think it is helpful.

Import Library

frommatpl­otlibimportpyplotasplt

Basic Line Plot

Subplots

The object that contains all subplots is called figure
Always put specific Attributes (color, markers, ..) for a subplot directly under plt.p­lot()

Linestyles

plt.pl­ot(x, y, sty­le­=' ')Keywords to put in for style:color= green, #AAAAAAline­sty­le= dotted: :, dashed: -- or -.mark­er= o, *, s, x, d, hline­wid­th= 1, 2, ..alpha= 0.1 - 1Boiler­plate Styles:plt.st­yle.us­e(­'­fiv­eth­irt­yei­ght­')plt.st­yle.us­e(­'­ggp­lot­')plt.st­yle.us­e(­'­sea­bor­n')plt.st­yle.us­e(­'­def­aul­t')

Legends

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loc specifies the legends location (if not specified: finds '­bes­t' location)

Figures

When we’re making lots of plots, it’s easy to end up with lines that have been plotted and not displa­yed. If we’re not careful, these “forgo­tten” lines will show up in your new plots. In order to be sure that you don’t have any stray lines, you can use the command plt.c­lo­se(­'al­l') to clear all existing plots before you plot a new one.

Modify Ticks

We have to do it this way, even if we only have one plot

Axis and Labels

Zoom in or out of the plot:plt.ax­is(­x_­min, x_max, y_min, y_max)Labeling the Axes:plt.xl­abe­l('str ')/ plt.yl­abel() / plt.ti­tle()

Add Text to Graph

Simple Bar Chart

plt.b­ar­(ra­nge­(le­n(y­_va­lues)), y_valu­es)We use rang­e(l­en(­y_v­alu­es)) to get a tick for each value we want to represent in the Bar Chart

Scatter Plot

Side-B­y-Side Bars

Stacked Bars

If we want to compare

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'di­fferent sub-at­tri­butes from one attrib­ute­' we can use stacked bar charts. For example:
Attr­ibu­te: Entert­ainment hours
Sub-­Att­rib­utes: Gaming, Reading, ..

Error Bars

If we want to present an uncert­ainty Range within a Bar Chart we can use Error Bars

Fill Between (Line Plot)

Returns a shaded are around the line

Pie Chart

Histogram

# Specify alpha for opacity or use hist­type to draw just the outline

Python Matplotlib Cheat Sheet Pdf

# Use line­width to specifiy the linewidth of the outline

Cheat Sheet Matplotlib

# Use the keyword normed to normalize the histog­rams
Norm­alize divides the x_values by a constat such that the area under the curve sums to 1

Matplotlib Cheat Sheet Pdf

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