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Binary file added Data Visualization/Bar Plotting.jpeg
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14 changes: 14 additions & 0 deletions Data Visualization/Bar Plotting/program.py
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# importing matplotlib module
from matplotlib import pyplot as plt

# x-axis values[x1, x2, x3, x4]
x = [5, 2, 9, 4, 7]

# y-axis values[y1, y2, y3, y4]
y = [10, 5, 8, 4, 2]

# Functions to plot
plt.bar(x,y)

#function to show the plot
plt.show()
Binary file added Data Visualization/Histo.png
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12 changes: 12 additions & 0 deletions Data Visualization/Histogram Plotting/program.py
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# importing matplotlib module
from matplotlib import pyplot as plt

# Y axis values
# [y1, y2, y3, y4]
y = [13, 1, 2, 6, 4]

#Function to plot Histogram
plt.hist(y)

#Function to show the plot
plt.show()
Binary file added Data Visualization/Line Plotting.jpeg
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14 changes: 14 additions & 0 deletions Data Visualization/Line Plotting/program.py
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# importing matplotlib module
from matplotlib import pyplot as plt

# x-axis values[x1, x2, x3, x4]
x = [5, 2, 9, 4, 7]

# y-axis values[y1, y2, y3, y4]
y = [10, 5, 8, 4, 2]

# Functions to plot
plt.plot(x,y)

#function to show the plot
plt.show()
7 changes: 7 additions & 0 deletions Data Visualization/Pie Chart Plotting/program.py
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import matplotlib.pyplot as plt
import numpy as np

y = np.array([35, 25, 25, 15])

plt.pie(y)
plt.show()
Binary file added Data Visualization/Pie.png
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31 changes: 31 additions & 0 deletions Data Visualization/README.md
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## Data Visulization

Data Visualization is the presentation of data in graphical format. It helps people understand the significance of data by summarizing and
presenting huge amount of data in a simple and easy-to-understand format and helps communicate information clearly and effectively.

## Setup Instruction

First Open the terminal and write `pip install matplotlib` this will install required package then after make file `program.py` and take any one program out of three and write it
and run the `program.py` file . Sit relax and enjoy Data Visualization Process


## Output Line Plotting

<img align="center" alt="JPEG" src="https://github.com/Ayush7614/Amazing-Python-Scripts/blob/master/Data%20Visualization/Line%20Plotting.jpeg" width="500" height="500" />

## Output Bar Plotting

<img align="center" alt="JPEG" src="https://github.com/Ayush7614/Amazing-Python-Scripts/blob/master/Data%20Visualization/Bar%20Plotting.jpeg" width="500" height="500" />

## Output Scatter Plotting

<img align="center" alt="JPEG" src="https://github.com/Ayush7614/Amazing-Python-Scripts/blob/master/Data%20Visualization/Scatter%20Plotting.jpeg" width="500" height="500" />

## Output Histogram Plotting

<img align="center" alt="PNG" src="https://github.com/Ayush7614/Amazing-Python-Scripts/blob/master/Data%20Visualization/Histo.png" width="500" height="500" />

## Output PieChart Plotting

<img align="center" alt="PNG" src="https://github.com/Ayush7614/Amazing-Python-Scripts/blob/master/Data%20Visualization/Pie.png" width="500" height="500" />

Binary file added Data Visualization/Scatter Plotting.jpeg
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9 changes: 9 additions & 0 deletions Data Visualization/Scatter Plotting/program.py
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# importing matplotlib module
from matplotlib import pyplot as plt

plt.plot([1, 2, 3, 4],
[1, 4, 9, 16], 'ro')

# ro to make red circles
plt.axis([0, 6, 0, 20])
plt.show()