8. Data Analysis - Visualization with Matplotlib

 Basic line plot

%matplotlib notebook -- to create visualization in jupyter notebook

import matplotlib.pyplot as plt

import numpy as np

X = np.arange(10)

plt.plot(X)

Create figure and Plot in two lines

1. Create Figure

fig = plt.figure()

2. Create Plot and add plot to figure

ax1 = fig.add_subplot(2,2,1)  --- 2 rows, 2 column and we are selecting 1st plot.

Without creating subplot ( plt.plot)

fig = plt.figure()

plt.plot(np.random.rand(50), 'k-') -- It will go to rightmost bottom.

Creating figure and axis in the same line.

fig, axes = plt.subplots(2,3)

axes[0,1].hist()

Creating same X and Y axis for all subplots.

fig, axes = plt.subplots(2,3, sharex=True, sharey = True)

Remove space between subplots.

fig, axes = plt.subplots(2,3, sharex=True, sharey = True, wspace =0, hspace=0)

Adding color and linestyle.

fig, axes = plt.subplots(2,3, sharex=True, sharey = True, wspace =0, hspace=0, linestyle ="--" , color ='r')

fig, axes = plt.subplots(2,3, sharex=True, sharey = True, wspace =0, hspace=0, "r--") -- short form.

Add Marker

fig, axes = plt.subplots(2,3, sharex=True, sharey = True, wspace =0, hspace=0, linestyle ="--" , color ='r', marker = "o")

Connecting 2 dots

fig, axes = plt.subplots(2,3, sharex=True, sharey = True, wspace =0, hspace=0, linestyle ="--" , color ='r', marker = "o", drawstyle="steps-post") -- steps-pre/steps-mid/steps

Add label

fig, axes = plt.subplots(2,3, sharex=True, sharey = True, wspace =0, hspace=0, linestyle ="--" , color ='r', marker = "o", drawstyle="steps-post", label="line")

X and Y axis label

fig = plt.figure()

ax1= fig.add_subplot(1,1,1)

ticks = ax1.set_xticks([0,10,20,30])

labels = ax1.set_xticklabels(["zero,", "ten","twnety","thirty"])

ax1.plot()

Change orientation and size of the X labels

fig = plt.figure()

ax1= fig.add_subplot(1,1,1)

ticks = ax1.set_xticks([0,10,20,30])

labels = ax1.set_xticklabels(["zero,", "ten","twnety","thirty"], rotation = 90, fontsize="large")

ax1.plot()

X-axis label, Title

ax1.set_xlabel("Xlabels")

ax1.set_title("Title)

Plots

veritical barplot

ax1.bar(["Car", "Truck", "Bus", "Auto"], [10,20,30,40]) -- Categorical + numeric data

horizontal bar plot

ax1.barh(["Car", "Truck", "Bus", "Auto"], [10,20,30,40]) -- Categorical + numeric data

histogram

ax1.hist(X, bin = 50)

pie chart

ax1.pie([10,20,30], labels=["car", "bus", "truck"])

scatter plot

ax1.scatter(x,y, marker="^", color="g")

Box/Violon plot

ax1.boxplot(X)

ax1.violinplot(X)