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Articles by Rishikesh Kumar Rishi
Page 34 of 102
How does parameters 'c' and 'cmap' behave in a Matplotlib scatter plot?
To get a sense of how the parameters c and cmap behave in a Matplotlib scatterplot, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Initialize a variable N to store the number of sample data.Create x and y data points using numpy.Plot x and y data points using scatter() method, color and colormap.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True N = 50 x = np.random.randn(N) y = np.random.randn(N) plt.scatter(x, y, c=x, ...
Read MoreCreating multiple boxplots on the same graph from a dictionary, using Matplotlib
To create multiple boxplots on the same graph from a dictionary, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make a dictionary, dict, with two columns.Create a figure and a set of subplots.Make a box and whisker plotSet the xtick labels using set_xticklabels() methodTo display the figure, use show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True data = {'col1': [3, 5, 2, 9, 1], 'col2': [2, 6, 1, 3, 4]} fig, ax = plt.subplots() ax.boxplot(data.values()) ax.set_xticklabels(data.keys()) plt.show()Output
Read MoreHow to edit the properties of whiskers, fliers, caps, etc. in a Seaborn boxplot in Matplotlib?
To edit the properties of whiskers, fliers, caps, etc. in a Seaborn boxplot, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make a dataframe using Pandas.Make a boxplot from the DataFrame columns.Get the boxplot's outliers, boxes, medians, and whiskers data.Print all the above data.To display the figure, use show() method.Exampleimport seaborn as sns import pandas as pd from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame(dict(age=[23, 45, 21, 15, 12])) _, bp = pd.DataFrame.boxplot(df, return_type='both') outliers = [flier.get_ydata() for flier ...
Read MoreHow to force Matplotlib to show the values on X-axis as integers?
To force matplotlib to show the values on X-axis as integers, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create two lists, x and y, of data points.Plot x and y using plot() method.Make a new list for only integers tick on X-axis. Use math.floor() and math.ceil() to remove the decimals and include only integers in the list.Set x and y labels.Set the title of the figure.To display the figure, use show() method.Exampleimport math from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True y ...
Read MoreHow to plot certain rows of a Pandas dataframe using Matplotlib?
To plot certain rows of a Pandas dataframe, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a Pandas data frame, df. It should be a two-dimensional, size-mutable, potentially heterogeneous tabular data.Make rows of Pandas plot. Use iloc() function to slice the df and print specific rows.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt import numpy as np import pandas as pd plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame(np.random.randn(10, 5), columns=list('abcde')) df.iloc[0:6].plot(y='e') print(df.iloc[0:6]) # plt.show()OutputWe have 10 rows in ...
Read MoreMoving X-axis in Matplotlib during real-time plot
To move X-axis in Matplotlib during real-time plot, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Create x and y data points using numpy.Plot x and y data points using plot() method.Make an animation by repeatedly calling a function *animate* that moves the X-axis during real-time plot.To display the figure, use show() method.Exampleimport matplotlib.pylab as plt import matplotlib.animation as animation import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig, ax = plt.subplots() x = np.linspace(0, 15, 100) ...
Read MoreDynamically updating a bar plot in Matplotlib
To update a bar plot dynamically in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure.Make a list of data points and colors.Plot the bars with data and colors, using bar() method.Using FuncAnimation() class, make an animation by repeatedly calling a function, animation, that sets the height of the bar and facecolor of the bars.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import animation as animation, pyplot as plt, cm plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = ...
Read MoreHow to draw more type of lines in Matplotlib?
To draw more type of lines in Matplotlib, 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 using numpy.Plot x and y data points using plot() method, with an array of dashes.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(-10, 10, 100) y = np.sin(x) plt.plot(x, y, dashes=[1, 1, 2, 1, 3], linewidth=7, color='red') plt.show()Output
Read MoreHow to move the legend to outside of a Seaborn scatterplot in Matplotlib?
To move the legend to outside of a Seaborn scatterplot, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make a Pandas dataframe with three coulmns, column1, column2 and column3.Draw a scatterplot with possibility of several semantic groupings.To place the legend outside the plot, use bbox_to_anchor in legend() method.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import pandas as pd import seaborn as sns plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame(dict(col1=[2, 1, 4], ...
Read MoreHow to set timeout to pyplot.show() in Matplotlib?
To set timeout to pyplot.show() in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a new backend-specific subclass of '.Timer'.Add a callback function that will be called whenever one of the plt.close() properties changes.Plot a list of data points.Start the timer.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() # set the timer interval 5000 milliseconds timer = fig.canvas.new_timer(interval = 5000) timer.add_callback(plt.close) plt.plot([1, 2, 3, 4, 5]) plt.ylabel('Y-axis Data') timer.start() plt.show()OutputThe ...
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