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Articles by Rishikesh Kumar Rishi
Page 10 of 102
How to write text in subscript in the axis labels and the legend using Matplotlib?
To write text in subscript in the axis labels and the legend, we can take the following steps −Create x and y data points using NumPy.Plot x and y data points with a super subscript texts label.Use xlabel and ylabel with subscripts in the text.Use the legend() method to place a legend in the plot.Adjust the padding between and around subplots.To display the figure, use the show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(1, 10, 1000) y = np.exp(x) plt.plot(x, y, label=r'$e^x$', c="red", lw=2) plt.xlabel("$X_{axis}$") plt.ylabel("$Y_{axis}$") plt.legend(loc='upper left') plt.show()Output
Read MoreHow to clear the memory completely of all Matplotlib plots?
Using the following methods, we can clear the memory occupied by Matplotlib plots.plt.figure() - Create a new figure or activate an existing figure.plt.figure().close() - Close a figure window.close() by itself closes the current figureclose(h), where h is a Figure instance, closes that figureclose(num) closes the figure number, numclose(name), where name is a string, closes figure with that labelclose('all') closes all the figure windowsplt.figure().clear() - It is the same as clf.plt.cla() - Clear the current axes.plt.clf() - Clear the current figure.Examplefrom matplotlib import pyplot as plt fig = plt.figure() plt.figure().clear() plt.close() plt.cla() plt.clf()OutputWhen we execute the code, it will clear all the plots from ...
Read MorePlot a bar using matplotlib using a dictionary
First, we can define our dictionary and then, convert that dictionary into keys and values. Finally, we can use the data to plot a bar chart.StepsCreate a dictionary, i.e., data, where milk and water are the keys.Get the list of keys of the dictionary.Get the list of values of the dictionary.Plot the bar using plt.bar().Using plt.show(), show the figure.Exampleimport matplotlib.pyplot as plt data = {'milk': 60, 'water': 10} names = list(data.keys()) values = list(data.values()) plt.bar(range(len(data)), values, tick_label=names) plt.show()Output
Read MorePlot multiple boxplots in one graph in Pandas or Matplotlib
To plot multiple boxplots in one graph in Pandas or Matplotlib, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Make a Pandas data frame with two columns.Plot the data frame using plot() method, with kind='boxplot'.To display the figure, use show() method.Exampleimport pandas as pd import numpy as np from matplotlib import pyplot as plt # Set the figure size plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True # Pandas dataframe data = pd.DataFrame({"Box1": np.random.rand(10), "Box2": np.random.rand(10)}) # Plot the dataframe ax = data[['Box1', 'Box2']].plot(kind='box', title='boxplot') # Display ...
Read MoreSave 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 get the correlation between two columns in Pandas?
We can use the .corr() method to get the correlation between two columns in Pandas. 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.Initialize two variables, col1 and col2, and assign them the columns that you want to find the correlation of.Find the correlation between col1 and col2 by using df[col1].corr(df[col2]) and save the correlation value in a variable, corr.Print the correlation value, corr.Exampleimport pandas as pd df = pd.DataFrame( { "x": [5, 2, 7, 0], "y": [4, ...
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 get nth row in a Pandas DataFrame?
To get the nth row in a Pandas DataFrame, we can use the iloc() method. For example, df.iloc[4] will return the 5th row because row numbers start from 0.StepsMake two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Print input DataFrame, df.Initialize a variable nth_row.Use iloc() method to get nth row.Print the returned DataFrame.Exampleimport pandas as pd df = pd.DataFrame( dict( name=['John', 'Jacob', 'Tom', 'Tim', 'Ally'], marks=[89, 23, 100, 56, 90], subjects=["Math", "Physics", "Chemistry", "Biology", "English"] ) ) ...
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