10 commonly used Matplotlib commands for data analytics

10 commonly used Matplotlib commands for data analytics

The data analysis process that involves identifying and correcting errors, inconsistencies, and missing values in a dataset.

plt.scatter(): This command is used to create scatter plots. It is useful for visualizing the relationship between two variables.

plt.plot()

plt.plot()

plt.bar():

plt.bar():

Title 2

This command is used to create bar plots. It is useful for comparing values across categories.

plt.hist():

plt.hist():

This command is used to create histograms. It is useful for visualizing the distribution of a single variable.

plt.boxplot()

plt.boxplot()

This command is used to create box plots. It is useful for visualizing the distribution of a variable across different categories.

plt.pie():

plt.pie():

This command is used to create pie charts. It is useful for visualizing the composition of a dataset.

  plt.subplots()

  plt.subplots()

This command is used to create a grid of plots. It is useful for comparing multiple plots side by side.

plt.xlabel()

plt.xlabel()

This command is used to set the label for the x-axis.

This command is used to set the label for the y-axis.

plt.ylabel()

plt.ylabel()

This command is used to set the title of the plot.

plt.title()

plt.title()

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