Matplotlib

%matplotlib inline

Plots

Image

import matplotlib.pyplot as plt

plt.imshow(arr)

Plot two lines that share the x axis

https://matplotlib.org/gallery/api/two_scales.html 

fig, ax1 = plt.subplots()

ax1.plot(x, y, 'r')

ax2 = ax1.twinx()

ax2.plot(x, y, 'b')

If you want the same scale:

ymin, ymax = y.min(), y.max()

ax1.set_ylim(ymin, ymax)

ax2.set_ylim(ymin, ymax)

Subplots

fig = plt.figure()

ax_array = fig.subplots(2, 2)

for i, process in enumerate([0.5, 1]):

    for j, noise in enumerate([1, 10]):

        r = ...

        r.plot(ax=ax_array[i, j])

        ax_array[i, j].set_title(f"process={process}, noise={noise}")

fig.tight_layout()

Reverse x axis

ax.invert_xaxis()

Bar Plot

fig = plt.figure(figsize=(8, 3))

plt.bar(x=df_students.Name, height=df_students.Grade, color='orange')

# Customize the chart

plt.title('Student Grades')

plt.xlabel('Student')

plt.ylabel('Grade')

plt.grid(color='#95a5a6', linestyle='--', linewidth=2, axis='y', alpha=0.7)

plt.xticks(rotation=90)

Axis

y ticks

ax.yaxis.set_ticks(np.arange(len(df)) + 1)

Interactive plots

%matplotlib widget

or

%matplotlib ipympl

Parameters

Setup parameters

https://matplotlib.org/3.3.2/tutorials/introductory/customizing.html 

import matplotlib as mpl

mpl.rcParams['axes.titlesize'] = 20

mpl.rcParams['axes.labelsize'] = 20

mpl.rcParams['ytick.labelsize'] = 15

mpl.rcParams['xtick.labelsize'] = 15

mpl.rcParams['legend.fontsize'] = 15

Format dates

fig.autofmt_xdate()

Format dollars

import matplotlib.ticker as ticker

revenue_formatter = ticker.StrMethodFormatter('${x:,.0f}')

ax.yaxis.set_major_formatter(revenue_formatter)

 Table

fig, ax = plt.subplots(figsize=(12, 4))

ax.axis("tight")

ax.axis("off")

table = ax.table(cellText=df.values, colLabels=df.columns, loc="center")

to pdf

from matplotlib.backends.backend_pdf import PdfPages

pp = PdfPages("file.pdf")

pp.savefig(fig, bbox_inches="tight")

pp.close()