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 11 of 102
How 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 MorePython Pandas – Find the maximum value of a column and return its corresponding row values
To find the maximum value of a column and to return its corresponding row values in Pandas, we can use df.loc[df[col].idxmax()]. Let's take an example to understand it better.StepsCreate a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Print the input DataFrame, df.Initialize a variable, col, to find the maximum value of that column.Find the maximum value and its corresponding row, using df.loc[df[col].idxmax()]Print the Step 4 output.Exampleimport pandas as pd df = pd.DataFrame( { "x": [5, 2, 7, 0], "y": [4, 7, 5, 1], "z": [9, 3, 5, 1] } ...
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 an array in Python using Matplotlib?
To plot an array in Python, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create two arrays, x and y, using numpy.Set the title of the curve using title() method.Plot x and y data points, with red color.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.array([5, 4, 1, 4, 5]) y = np.sort(x) plt.title("Line graph") plt.plot(x, y, color="red") 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
Read MoreHow can I plot a single point in Matplotlib Python?
To plot a single data point in matplotlib, we can take the following steps −Initialize a list for x and y with a single value.Limit X and Y axis range for 0 to 5.Lay out a grid in the current line style.Plot x and y using plot() method with marker="o", markeredgecolor="red", markerfacecolor="green".To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = [4] y = [3] plt.xlim(0, 5) plt.ylim(0, 5) plt.grid() plt.plot(x, y, marker="o", markersize=20, markeredgecolor="red", markerfacecolor="green") plt.show()Output
Read MoreHow to append two DataFrames in Pandas?
To append the rows of one dataframe with the rows of another, we can use the Pandas append() function. With the help of append(), we can append columns too. Let's take an example and see how to use this method.StepsCreate a two-dimensional, size-mutable, potentially heterogeneous tabular data, df1.Print the input DataFrame, df1.Create another DataFrame, df2, with the same column names and print it.Use the append method, df1.append(df2, ignore_index=True), to append the rows of df2 with df2.Print the resultatnt DataFrame.Exampleimport pandas as pd df1 = pd.DataFrame({"x": [5, 2], "y": [4, 7], "z": [9, 3]}) df2 = pd.DataFrame({"x": [1, 3], "y": ...
Read More