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# Special Plot Types

Line Chart, Bar Chart, Pie Chart. Matplotlib allows you to create different kinds of plots ranging from histograms and scatter plots to bar graphs and bar charts.

Special Plot Types

Matplotlib allows you to create different kinds of plots ranging from histograms and scatter plots to bar graphs and bar charts.

## Line Chart

A Line Chart or Line Graph is a type of chart which displays information as a series of data points called ‘markers’ connected by straight line segments. A Line Chart is often used to visualize a trend in data over intervals of time – a time series – thus the line is often drawn chronologically.

Example: Line plot

import matplotlib.pyplot as plt

years = [2014, 2015, 2016, 2017, 2018]

total_populations = [8939007, 8954518, 8960387, 8956741, 8943721]

plt.plot (years, total_populations)

plt.title ("Year vs Population in India")

plt.xlabel ("Year")

plt.ylabel ("Total Population")

plt.show()

In this program,

Plt.title() → specifies title to the graph

Plt.xlabel() → specifies label for X-axis

Plt.ylabel() → specifies label for Y-axis

Output ## Bar Chart

A BarPlot (or BarChart) is one of the most common type of plot. It shows the relationship between a numerical variable and a categorical variable.

Bar chart represents categorical data with rectangular bars. Each bar has a height corresponds to the value it represents. The bars can be plotted vertically or horizontally. It’s useful when we want to compare a given numeric value on different categories. To make a bar chart with Matplotlib, we can use the plt.bar() function.

Example

import matplotlib.pyplot as plt

# Our data

labels = ["TAMIL", "ENGLISH", "MATHS", "PHYSICS", "CHEMISTRY", "CS"] usage = [79.8, 67.3, 77.8, 68.4, 70.2, 88.5]

#Generating the y positions. Later, we'll use them to replace them with labels. y_positions = range (len(labels))

#Creating our bar plot

plt.bar (y_positions, usage)

plt.xticks (y_positions, labels)

plt.ylabel ("RANGE")

plt.title ("MARKS")

plt.show()

Output The above code represents the following:

Labels → Specifies labels for the bars.

Usgae → Assign values to the labels specified.

Xticks → Display the tick marks along the x-axis at the values represented. Then specify the label for each tick mark.

Range → Create sequence of numbers.

## Key Differences Between Histogram and Bar Graph

The differences between Histogram and bar graph are as follows

1. Histogram refers to a graphical representation; that displays data by way of bars to show the frequency of numerical data. A bar graph is a pictorial representation of data that uses bars to compare different categories of data.

2. A histogram represents the frequency distribution of continuous variables. Conversely, a bar graph is a diagrammatic comparison of discrete variables.

3. Histogram presents numerical data whereas bar graph shows categorical data.

4. The histogram is drawn in such a way that there is no gap between the bars. On the ot her hand, there is proper spacing between bars in a bar graph that indicates discontinuity.

5. Items of the histogram are numbers, which are categorised together, to represent ranges of data. As opposed to the bar graph, items are considered as individual entities.

6. In the case of a bar graph, it is quite common to rearrange the blocks, from highest to lowest. But with histogram, this cannot be done, as they are shown in the sequence of classes.

7. The width of rectangular blocks in a histogram may or may not be same while the width of the bars in a bar graph is always same.

## Pie Chart

Pie Chart is probably one of the most common type of chart. It is a circular graphic which is divided into slices to illustrate numerical proportion. The point of a pie chart is to show the relationship of parts out of a whole.

To make a Pie Chart with Matplotlib, we can use the plt.pie() function. The autopct parameter allows us to display the percentage value using the Python string formatting.

Example

import matplotlib.pyplot as plt

sizes = [89, 80, 90, 100, 75]

labels = ["Tamil", "English", "Maths", "Science", "Social"]

plt.pie (sizes, labels = labels, autopct = "%.2f ")

plt.axes().set_aspect ("equal") plt.show() Tags : Line Chart, Bar Chart, Pie Chart , 12th Computer Science : UNIT 16 : Integrating Python with MySql and C++ : Data Visualization Using Pyplot: Line Chart, Pie Chart and Bar Chart
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12th Computer Science : UNIT 16 : Integrating Python with MySql and C++ : Data Visualization Using Pyplot: Line Chart, Pie Chart and Bar Chart : Special Plot Types | Line Chart, Bar Chart, Pie Chart