To add a 3D subplot to a matplotlib figure, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create x, y and z data points using numpy.Create a new figure or activate an existing figure.Add an 'ax' to the figure as ... Read More

To set labels in matplotlib.hlines, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Add a horizontal line across the axis, y=1, with y=1 label, color='orange'.Add a horizontal line across the axis, y=2, with y=2 label, color='red'.To display the figure, use ... Read More

To make a scatter plot for clustering in Python, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create x and y data points, Cluster and centers using numpy.Create a new figure or activate an existing figure.Add a subplot arrangement to ... Read More

To put a circle with annotation in matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create data points using numpy.Get the point coordinate to put circle with annotation.Get the current axis.Plot the data and data points using plot() method.Set ... Read More

To get a 3D plot, we can use fig.add_subplot(111, projection='3d') method to instantiate the axis. After that, we can use the scatter method to draw different data points on the x, y, and z axes.StepsCreate a new figure, or activate an existing figure.Add an `~.axes.Axes` to the figure as part of ... Read More

We can use the shift() method in Pandas to shift the columns of a DataFrame without having to rewrite the whole DataFrame. shift() takes the following parametersshift(self, periods=1, freq=None, axis=0, fill_value=None)periods  Number of periods to shift. It can take a negative number too.axis  It takes a Boolean value; 0 if ... Read More

To find numeric columns in Pandas, we can make a list of integers and then include it into select_dtypes() method. Let's take an example and see how to apply this method.StepsCreate a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Print the input DataFrame, df.Make a list of data type, i.e., numerics, ... Read More

A regular expression (regex) is a sequence of characters that define a search pattern. To filter rows in Pandas by regex, we can use the str.match() method.StepsCreate a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Print the input DataFrame, df.Initialize a variable regex for the expression. Supply a string value as ... Read More

It's quite simple to rename a DataFrame column name in Pandas. All that you need to do is to use the rename() method and pass the column name that you want to change and the new column name. Let's take an example and see how it's done.StepsCreate a two-dimensional, size-mutable, ... Read More

To access a group of rows in a Pandas DataFrame, we can use the loc() method. For example, if we use df.loc[2:5], then it will select all the rows from 2 to 5.StepsCreate a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Print the input DataFrame, df.Use df.loc[2:5] to select the rows ... Read More