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Articles by Rishikesh Kumar Rishi
1,016 articles
Matplotlib legends in subplot
To add legends in a subplot, we can take the following Steps −Using numpy, create points for x, y1, y2 and y3.Create a figure and a set of subplots, using the subplots() method, considering 3 subplots.Plot the curve on all the subplots(3), with different labels, colors. To place the legend for each curve or subplot adding label.To activate label for each curve, 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(-2, 2, 100) y1 = np.sin(x) y2 = np.cos(x) y3 ...
Read MoreHow to plot multiple graphs in Matplotlib?
To plot multiple graphs in matplotlib, we will use the following steps −StepsCreate x, y1 and y2 data points using numpy.Add a subplot to the current figure at index 1.Plot curve 1 using x and y1.Add a subplot to the current figure at index 2.Plot curve 2 using x and y2.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, 10) y1 = np.sin(x) y2 = np.cos(x) plt.subplot(211) plt.plot(y1) plt.subplot(212) plt.plot(y2) plt.show()Output
Read MoreHow to change the color of the axis, ticks and labels for a plot in matplotlib?
We can change the color of the axis, ticks and labels, using ax.spines['left'].set_color('red') and ax.spines['top'].set_color('red') statements. To change the color of the axis, ticks, and labels for a plot in matplotlib, we can take the following steps −Create a new figure, or activate an existing figure, using plt.figure().Add an axis to the figure as part of a subplot arrangement, using plt.add_subplot(xyz) where x is nrows, y is ncols and z is the index. Here taking x = 1(rows), y = 2(columns) and z = 1(position).Set up X-axis and Y-axis labels using set_xlabel and set_ylabel method for creating ax using add_subplot().To ...
Read MoreHow to save Pandas data into Excel multiple sheets?
To save Pandas DataFrames into multiple excel sheets, we can use the pd.ExcelWriter() method. Make sure you have the openpyxl package installed before using ExcelWriter().StepsCreate a two-dimensional, size-mutable, potentially heterogeneous tabular data, df1.Print the input DataFrame, df1.Create another DataFrame, df2, and print it.Use ExcelWriter() method to write the given formatted cells into an Excel sheet.Exampleimport pandas as pd df1 = pd.DataFrame( [[5, 2], [4, 1]], index=["One", "Two"], columns=["Rank", "Subjects"] ) df2 = pd.DataFrame( [[15, 21], [41, 11]], index=["One", "Two"], columns=["Rank", ...
Read MoreHow 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 MoreHow to get a value from the cell of a Pandas DataFrame?
To get a value from the cell of a DataFrame, we can use the index and col variables.StepsCreate a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Print the input DataFrame, df.Initialize the index variable.Initialize the col variable.Get the cell value corresponding to index and col variable.Print the cell value.Example Live Demoimport pandas as pd df = pd.DataFrame( { "x": [5, 2, 1, 9], "y": [4, 1, 5, 10], "z": [4, 1, 5, 0] } ) print("Input DataFrame is:", df) index = 2 col = "y" cell_val = df.iloc[index][col] print ...
Read MoreHow to select all columns except one in a Pandas DataFrame?
To select all columns except one column in Pandas DataFrame, we can use df.loc[:, df.columns != ].StepsCreate a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Print the input DataFrame, df.Initialize a variable col with column name that you want to exclude.Use df.loc[:, df.columns != col] to create another DataFrame excluding a particular column.Print the DataFrame without col column.Example Live Demoimport pandas as pd df = pd.DataFrame( { "x": [5, 2, 1, 9], "y": [4, 1, 5, 10], "z": [4, 1, 5, 0] } ) print("Input DataFrame is:", df) col ...
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 ...
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