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 16 of 102
How to increase the line thickness of a Seaborn Line?
To increase the line thickness of a Seaborn line, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a dataframe, df, of two-dimensional, size-mutable, potentially heterogeneous tabular data.Create a Seaborn line plot with linewidth value in the argument. Here we have set linewidth=7.Rotate the tick params, i.e., labels by 45 degrees.To display the figure, use Show() method.Exampleimport seaborn as sns from matplotlib import pyplot as plt import pandas as pd import numpy as np plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame( dict( ...
Read MoreHow to adjust the space between Matplotlib/Seaborn subplots for multi-plot layouts?
To adjust the space between matplotlib/seaborn subplots for multi-plot layouts, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Adjust the subplot layout parameters.Create Seaborn's box plot for all the subplots.To display the figure, use Show() method.Exampleimport seaborn as sns from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig, axes = plt.subplots(2, 2) # Adjust the subplot layout parameters fig.subplots_adjust(hspace=0.125, wspace=0.125) # Create Seaborn boxplot for all the subplots sns.boxplot(ax=axes[0, 0]) sns.boxplot(ax=axes[0, 1]) sns.boxplot(ax=axes[1, 0]) sns.boxplot(ax=axes[1, ...
Read MoreHow to sort a boxplot by the median values in Pandas?
To sort a boxplot by the median values in Pandas, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a Pandas dataframe of two-dimensional, size-mutable, potentially heterogeneous tabular data, with three columns.Group the dataframe elements by marks and dob.Find the median of the dataframe.Get the sorted values of the median.Create a box plot from the DataFrame columns.To display the figure, use Show() method.Exampleimport pandas as pd import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame([ [23, 'James', 12], [39, 'Jimmy', ...
Read MoreHow to make a grouped boxplot graph in matplotlib?
To make a grouped boxplot graph in matplotlib, we can take the following steps −Import matplotlib.pyplot and seaborn.Set the figure size and adjust the padding between and around the subplots.Load an example Seaborn dataset from the online repository.Make a boxplot with male and female group in a single day.To display the figure, use show() method.Exampleimport seaborn as sns import matplotlib.pyplot as plt # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Import a Seaborn dataset data = sns.load_dataset('tips') # Create a grouped boxplot sns.boxplot(x=data['day'], y=data['total_bill'], hue=data['sex']) plt.show()OutputIt will produce the following ...
Read MoreHow to plot int to datetime on X-axis using Seaborn?
To plot int to datetime on X-axis using Seaborn in matplotlib, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a dataframe, df, of two-dimensional, size-mutable, potentially heterogeneous tabular data, with three columns.Create a countplot with int, i.e., dob on the X-axis.Set int to datetime label on the X-axis.To display the figure, use Show() method.Exampleimport seaborn as sns from matplotlib import pyplot as plt import pandas as pd import numpy as np # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Data frame with 3 ...
Read MoreHow to build colorbars without attached plot in matplotlib?
To build colorbars without attached plot in matplotlib, we can take the following steps.StepsSet the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Adjust the subplot layout parameters.Normalize the quaternion in place. Return the norm of the quaternion.Get the colorbar instance (cb) with base colorbar and horizontal orientation.To display the figure, use Show() method.Exampleimport matplotlib.pyplot as plt import matplotlib as mpl # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Create a figure and a set of subplots fig, ax = plt.subplots() # Adjust ...
Read MoreHow to cycle through both colours and linestyles on a matplotlib figure?
To cycle through both colors and linestyles on a matplotlib figure, we can take the following steps.StepsSet the figure size and adjust the padding between and around the subplots.Set the current rcParams, withcolors and linestyle.Plot the data points using plot() method.To display the figure, use Show() method.Exampleimport matplotlib.pyplot as plt from cycler import cycler # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Set the rcParams with color or linestyle plt.rc('axes', prop_cycle=(cycler('color', ['r', 'g', 'b', 'y']) + cycler('linestyle', [':', '-.', '-', '--']))) # Plot the data points plt.plot([0, 5, 2, ...
Read MoreHow to better rasterize a plot without blurring the labels in matplotlib?
To rasterize a plot in a bettery way without blurring the labels in matplotlib, we can take the following steps.StepsSet the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Axis 0 – Fill the area between the curve with alpha and rasterized=False.Add text to the axes.Axis 1 – Fill the area between the curve with alpha and rasterized=True.Add text to the axes.Axes 2 and 3 – Fill the area between the curve without alpha and rasterized=True and False, respectively.Add text to the axes.To display the figure, use Show() method.Exampleimport matplotlib.pyplot as ...
Read MoreHow to get the properties of a picked object in mplot3d (matplotlib + python)?
To get the properties of picked objects in matplotlib 3d, we can take the following steps.StepsSet the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure.Add an 'ax' to the figure as part of a subplot arrangement.Make a scatter plot of random data points.Bind the function *pick_event_method* to the event *pick_event*.Print x, y and z coordinates of the event.To display the figure, use Show() method.Exampleimport matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() ax = fig.add_subplot(111, projection='3d') ...
Read MorePlotting profile histograms in Python Matplotlib
In a profile histogram, each bin contains the mean of its entries. To plot profile histograms in Python, we can use the regplot method from Seaborn.StepsSet the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.Use seaborn.regplot to plot the data and a linear regress model fit. Use the parameter x_bins to bin the x variable into discrete bins. Use fit_reg=True to plot the regression model relating the x and y variables.To display the figure, use Show() method.Exampleimport numpy as np import seaborn as sns from matplotlib import pyplot as plt ...
Read More