<jupyter_start><jupyter_text>Important Plots in Data Visualization 1. Scatter Plot2. Bar Graph3. Pie Chart 1. Scatter Plot<jupyter_code># Scatter Plot
x = 100 + np.random.randn(50)
y = 100 + np.random.randn(50)

plt.scatter(x,y)
plt.xlabel('X-Value')
plt.ylabel('Y-Value')
plt.title('Scatter Plot')
plt.show()<jupyter_output><empty_output><jupyter_text>2. Bar Graph<jupyter_code># Bar Graph
x = ['Jan','Feb','Mar','Apr','May']
y = [100,200,156,234,850]

plt.bar(x,y)
plt.title('Phone Sale')
plt.xlabel('Months')
plt.ylabel('Number of Phones Sold')
plt.show()<jupyter_output><empty_output><jupyter_text>3. Pie Chart<jupyter_code># Pie Chart
sports = ['Cricket','Football','Hockey','Tennis','Basketball']
players = [964,266,852,860,746]

plt.pie(players, labels=sports, autopct='%.2f%%')
plt.show()
plt.pie?  # how it's work<jupyter_output><empty_output>
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