Article Categories
- All Categories
-
Data Structure
-
Networking
-
RDBMS
-
Operating System
-
Java
-
MS Excel
-
iOS
-
HTML
-
CSS
-
Android
-
Python
-
C Programming
-
C++
-
C#
-
MongoDB
-
MySQL
-
Javascript
-
PHP
-
Economics & Finance
Articles by Rishikesh Kumar Rishi
Page 33 of 102
How to create a matplotlib colormap that treats one value specially?
To create a matplotlib colormap that treats one value specially, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Get a colormap instance, name is "rainbow".Set the color for low out-of-range values, using set_under('red') method.Create random data and eps using numpy.Create a figure and a set of subplots.Display data as an image, i.e., on a 2D regular raster, using imshow() method.Create a colorbar for a ScalarMappable instance, im.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True cmap ...
Read MoreHow to show a figure that has been closed in Matplotlib?
To show a figure that has been closed in Matplotlib, we can create a new Canvas Manager and store the previous figure into a new Canvas figure.StepsSet the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure.Create x and y data points using numpy.Plot x and y data points using plot() method.Close the current figure where the plot has been plotted.Now, store the previous figure in a new Canvas figure.Set the Canvas that contains the figure.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as ...
Read MoreHow to set the Y-axis in radians in a Python plot?
To set the Y-axis in radians in a Python plot, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create x and y data point using numpy.Create a new figure or activate an existing figure using figure() method.Add an axes, ax, to the figure as part of a subplot arrangement.Get the list of Y-axis ticks and ticklabels.Set the ticks and ticklabels using set_yticks() and set_yticklabels() methods.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.arange(-10.0, ...
Read MoreHow can box plot be overlaid on top of swarm plot in Seaborn?
To plot a Box plot overlaid on top of a Swarm plot in Seaborn, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a Pandas dataframe, i.e., two-dimensional, size-mutable, potentially heterogeneous tabular data.Initialize the plotter, swarmplot.To plot the box plot, use boxplot() method.To display the figure, use show() method.Exampleimport seaborn as sns import matplotlib.pyplot as plt import pandas as pd import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True data = pd.DataFrame({"Box1": np.arange(10), "Box2": np.arange(10)}) ax = sns.swarmplot(x="Box1", y="Box2", data=data, zorder=0) sns.boxplot(x="Box1", y="Box2", data=data, showcaps=False, ...
Read MoreAdjust the width of box in boxplot in Python Matplotlib
To adjust the width of box in boxplot in Python matplotlib, we can use width in the boxplot() method.StepsSet the figure size and adjust the padding between and around the subplots.Make a Pandas dataframe, i.e., two-dimensional, size-mutable, potentially heterogeneous tabular data.Make a box and whisker plot, using boxplot() method with width tuple to adjust the box in boxplot.To display the figure, use show() method.Exampleimport pandas as pd import numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True data = pd.DataFrame({"Box1": np.random.rand(10), "Box2": np.random.rand(10)}) ax = plt.boxplot(data, widths=(0.25, 0.5)) plt.show()Output
Read MoreHow to draw a heart with pylab?
To draw a heart with pylab/pyplot, we can follow the steps given below −StepsSet the figure size and adjust the padding between and around the subplots.Create x, y1 and y2 data points using numpy.Fill the area between (x, y1) and (x, y2) using fill_between() method.Place text on the plot using text() method at (0, -1.0) point.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 x = np.linspace(-2, 2, 1000) y1 = np.sqrt(1 - (abs(x) - 1) ** 2) y2 = -3 * np.sqrt(1 - ...
Read MoreHow to automatically annotate the maximum value in a Pyplot?
To annotate the maximum value in a Pyplot, 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 x and y data points.Plot x and y data points using numpy.Find the maximum in Y array and position corresponding to that max element in the arrayAnnotate that point with local max.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 fig = plt.figure() ax = fig.add_subplot(111) x ...
Read MoreHow to color a Seaborn boxplot based on DataFrame column name in Matplotlib?
To color a Seaborn boxplot based on dataframe column name, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make a Pandas dataframe with two columns, col1 and col2.Make a boxplot with horizontal orientation.Get the boxes artists.Iterate the boxes and set the facecolor of the box.To display the figure, use show() method.Exampleimport seaborn as sns import matplotlib.pyplot as plt import pandas as pd plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame( [[2, 4], [7, 2] ...
Read MoreHow to draw rounded line ends using Matplotlib?
To draw rounded line ends using matplotlib, we can use solid_capstyle='round'.StepsSet the figure size and adjust the padding between and around the subplots.Create random x and y data points using numpy.Create a figure and a set of subplots.Plot x and y data points using plot() method, with solid_capstyle in the method argument.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.random.randn(5) y = np.random.randn(5) fig, ax = plt. subplots() ln, = ax.plot(x, y, lw=10, solid_capstyle='round', color='red') plt.show()Output
Read MorePlot 95% confidence interval errorbar Python Pandas dataframes in Matplotlib
To plot 95% confidence interval errorbar Python Pandas dataframes, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Get a dataframe instance of two-dimensional, size-mutable, potentially heterogeneous tabular data.Make a dataframe with two columns, category and number.Find the mean and std of category and number.Plot y versus x as lines and/or markers with attached errorbars.To display the figure, use show() method.Exampleimport numpy as np import pandas as pd import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame() df['category'] = np.random.choice(np.arange(10), 1000, replace=True) df['number'] = ...
Read More