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 64 of 102
What is the simplest way to make Matplotlib in OSX work in a virtual environment?
To make matplotlib in OSX work in a virtual environment, we can first create a virtual environment and then activate that created environment. Thereafter, install all the dependencies in that virtual environment.StepsOpen ubuntu terminal.apt-get install python-venvpython -m venv source /bin/activate
Read MoreHow to plot a stacked event duration using Python Pandas?
To plot a stacked event duration using Python Pandas, we can take the following stepsSet the figure size and adjust the padding between and around the subplots.Create a dataframe with lists of xmin and its corresponding xmax.Use hlines() method to plot a stacked event duration.To display the figure, use show() method.Exampleimport pandas as pd from datetime import datetime as dt from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame(dict(xmin=[dt.strptime('1994-07-19', '%Y-%m-%d'), dt.strptime('2006-03-16', '%Y-%m-%d'), dt.strptime('1980-10-31', '%Y-%m-%d'), dt.strptime('1981-06-11', '%Y-%m-%d'), dt.strptime('2006-06-28', '%Y-%m-%d')], ...
Read MoreHow to close a Python figure by keyboard input using Matplotlib?
To close a Python figure by a keyboard input, we can use plt.pause() method, an input, and close() method.StepsSet the figure size and adjust the padding between and around the subplots.Create random t and y data points using numpy.Create a new figure or activate an existing figure using figure() method.Plot t and y data points using plot() method.Set the title of the plot.Redraw the current figure using draw() method.Run a true loop to pause the current figure.Take input from the user to go to the next statement.Use close() method to close the figure.Exampleimport numpy as np from matplotlib import pyplot ...
Read MoreHow can I display an np.array with pylab.imshow() using Matplotlib?
To display an np.array with imshow(), we can take the following stepsSet the figure size and adjust the padding between and around the subplots.Make a 2D data raster using an np.array.Display the data as an image, i.e., on a 2D regular raster.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 data = np.array( [[0.1, 0.7, 0.6, 0.3], [0.2, 0.6, 0.5, 0.2], [0.8, 0.3, 0.80, 0.01], [0.3, 0.4, 0.2, 0.1]] ) plt.imshow(data, interpolation="nearest", cmap="RdYlGn_r") plt.show()Output
Read MoreIncreasing the space for X-axis labels in Matplotlib
To increase the space for X-axis labels in Matplotlib, we can use the spacing variable in subplots_adjust() method's argument.StepsSet the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure using figure() method.Create x and y data points using numpy.Plot x and y using plot() method.Put xlabel using xlabel() method with LaTex expression.Use subplots_adjust() method to increase or decrease the space for X-axis labelsTo 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 fig = plt.figure() x = ...
Read MoreHow to set Dataframe Column value as X-axis labels in Python Pandas?
To set Dataframe column value as X-axis labels in Python Pandas, we can use xticks in the argument of plot() method.StepsSet the figure size and adjust the padding between and around the subplots.Make a dataframe using Pandas with column1 key.Plot the Pandas dataframe using plot() method with column1 as the X-axis column.To display the figure, use show() method.Exampleimport pandas as pd from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True data = pd.DataFrame({"column1": [4, 6, 7, 1, 8]}) data.plot(xticks=data.column1) plt.show()Output
Read MorePlot a polar color wheel based on a colormap using Python/Matplotlib
To plot a color wheel based on a colormap using Python/Matplotlib, we can use the colorbar class and can use copper colormap.StepsSet the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure using figure() method.Add an axes to the figure using add_axes() method.Set the direction of the axes.Linearly normalize the data using Normalize class.Draw a colorbar in an existing axes.Set the artist's visibility.Turn the X- and Y-axis off.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt, cm, colors, colorbar plt.rcParams["figure.figsize"] = [7.50, 3.50] ...
Read MoreConnecting two points on a 3D scatter plot in Python and Matplotlib
To connect two points on a 3D scatter plot, we can take the following stepsSet the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure using figure() method.Add an axes to the current figure as a subplot arrangement.Create lists for x, y and z.Plot x, y and z data points using scatter() methodTo connect the points, use plot() method with x, y and z data points with black color line.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 fig = ...
Read MoreHow to plot statsmodels linear regression (OLS) cleanly in Matplotlib?
We can plot statsmodels linear regression (OLS) with a non-linear curve but with linear data.StepsSet the figure size and adjust the padding between and around the subplots.To create a new one, we can use seed() method.Initialize the number of sample and sigma variables.Create linear data points x, X, beta, t_true, y and res using numpy.Res is an ordinary Least Square class instance.Calculate the standard deviation. Confidence interval for prediction applies to WLS and OLS, not to general GLS, that is, independently but not identically distributed observations.Create a figure and a set of subplots using subplot() method.Plot all the curves using ...
Read MoreControlling the alpha value on a 3D scatter plot using Python and Matplotlib
To control the alpha value on a 3D scatter plot using Python and Matplotlib, we can set the facecolor and edgecolors value.Set the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure using figure() method.Add an '~.axes.Axes' to the figure as part of a subplot arrangement.Create x, y and z data points using numpy.Plot x, y and z points using scatter() method.Set the facecolors and edgecolors.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 ...
Read More