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Matplotlib Articles
Page 3 of 91
Save the plots into a PDF in matplotlib
Using plt.savefig("myImagePDF.pdf", format="pdf", bbox_inches="tight") method, we can save a figure in PDF format.StepsCreate a dictionary with Column 1 and Column 2 as the keys and Values are like i and i*i, where i is from 0 to 10, respectively.Create a data frame using pd.DataFrame(d), d created in step 1.Plot the data frame with ‘o’ and ‘rx’ style.To save the file in PDF format, use savefig() method where the image name is myImagePDF.pdf, format = ”pdf”.To show the image, use the plt.show() method.Exampleimport pandas as pd from matplotlib import pyplot as plt d = {'Column 1': [i for i in ...
Read MoreHow to hide axes and gridlines in Matplotlib?
To hide axes (X and Y) and gridlines, we can take the following steps −Create x and y points using numpy.Plot a horizontal line (y=0) for X-Axis, using the plot() method with linestyle, labels.Plot x and y points using the plot() method with linestyle, labels.To hide the grid, use plt.grid(False).To hide the axes, use plt.axis('off')To activate the labels' legend, use the legend() method.To display the figure, use the 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 x = np.linspace(-10, 10, 50) y = np.sin(x) plt.axhline(y=0, c="green", linestyle="dashdot", label="y=0") plt.plot(x, y, c="red", lw=5, linestyle="dashdot", label="y=sin(x)") plt.grid(False) plt.axis('off') ...
Read MoreHow to remove or hide X-axis labels from a Seaborn / Matplotlib plot?
To remove or hide X-axis labels from a Seaborn / Matplotlib plot, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Use sns.set_style() to set an aesthetic style for the Seaborn plot.Load an example dataset from the online repository (requires Internet).To hide or remove X-axis labels, use set(xlabel=None).To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt import seaborn as sns plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True sns.set_style("whitegrid") tips = sns.load_dataset("tips") ax = sns.boxplot(x="day", y="total_bill", data=tips) ax.set(xlabel=None) plt.show()Output
Read MoreHow do you create line segments between two points in Matplotlib?
To create line segments between two points in matplotlib, we can take the following stepsSet the figure size and adjust the padding between and around the subplots.To make two points, create two lists.Extract x and y values from point1 and point2.Plot x and y values using plot() method.Place text for both the points.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 point1 = [1, 2] point2 = [3, 4] x_values = [point1[0], point2[0]] y_values = [point1[1], point2[1]] plt.plot(x_values, y_values, 'bo', linestyle="--") plt.text(point1[0]-0.015, point1[1]+0.25, "Point1") plt.text(point2[0]-0.050, point2[1]-0.25, "Point2") plt.show()Output
Read MoreHow to change the range of the X-axis and Y-axis in Matplotlib?
To change the range of X and Y axes, we can use xlim() and ylim() methods.StepsSet 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.Set the X and Y axes limit.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(-15, 15, 100) y = np.sin(x) plt.plot(x, y) plt.xlim(-10, 10) plt.ylim(-1, 1) plt.show()Output
Read MorePlotting dates on the X-axis with Python\'s Matplotlib
Using Pandas, we can create a dataframe and can set the index for datetime. Using gcf().autofmt_xdate(), we will adjust the date on the X-axis.StepsMake the list of date_time and convert into it in date_time using pd.to_datetime().Consider data = [1, 2, 3]Instantiate DataFrame() object, i.e., DF.Set the DF['value'] with data from step 2.Set DF.index() using date_time from step 1.Now plot the data frame i.e., plt.plot(DF).Get the current figure and make it autofmt_xdate().Using plt.show() method, show the figure.Exampleimport pandas as pd import matplotlib.pyplot as plt date_time = ["2021-01-01", "2021-01-02", "2021-01-03"] date_time = pd.to_datetime(date_time) data = [1, 2, 3] DF = ...
Read MoreHow to make two plots side-by-side using Python?
Using subplot(row, col, index) method, we can split a figure in row*col parts, and can plot the figure at the index position. In the following program, we will create two diagrams in a single figure.StepsCreating x, y1, y2 points using numpy.With nrows = 1, ncols = 2, index = 1, add subplot to the current figure, using the subplot() method.Plot the line using x and y1 points, using the plot() method.Set up the title, label for X and Y axes for Figure 1, using plt.title(), plt.xlabel(), and plt.ylabel() methods.With nrows = 1, ncols = 2, index = 2, add subplot ...
Read MoreHow to plot CSV data using Matplotlib and Pandas in Python?
To plot CSV data using Matplotlib and Pandas in Python, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make a list of headers of the .CSV file.Read the CSV file with headers.Set the index and plot the dataframe.To display the figure, use show() method.Exampleimport pandas as pd import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True headers = ['Name', 'Age', 'Marks'] df = pd.read_csv('student.csv', names=headers) df.set_index('Name').plot() plt.show()Output
Read MoreHow to label a line in Matplotlib (Python)?
To label a line in matplotlib, we can use label in the argument of plot() method,StepsSet the figure size and adjust the padding between and around the subplots.Plot with label="line1" using plot() method.Plot with label="line2" using plot() method.To place a legend on the figure, use legend() method.To 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 line1, = plt.plot([1, 2, 3], label="line1") line2, = plt.plot([3, 2, 1], label="line2") leg = plt.legend(loc='upper center') plt.show()Output
Read MoreHow to plot a function defined with def in Python? (Matplotlib)
To plot a function defined with def in Python, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a user-defined function using, def, i.e., f(x).Create x data points using numpy.Plot x and f(x) using plot() method.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 def f(x): return np.sin(x) + x + x * np.sin(x) x = np.linspace(-10, 10, 100) plt.plot(x, f(x), color='red') plt.show()Output
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