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To get the (x, y) positions pointing with mouse in an interactive plot, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure.Bind the function *mouse_event* to the event *button_press_event*.Create x and y data points using numpy.Plot the x and y data points using plot() method.To display the figure, use Show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True def mouse_event(event): print('x: {} and y: {}'.format(event.xdata, event.ydata)) fig = ... Read More
To return vector of label values using level name in the MultiIndex, use the MultiIndex.get_level_values() method in Pandas.At first, import the required libraries −import pandas as pdMultiIndex is a multi-level, or hierarchical, index object for pandas objects −multiIndex = pd.MultiIndex.from_arrays([list('pqrrss'), list('strvwx')], names=['One', 'Two'])Display the MultiIndex −print("The MultiIndex...", multiIndex) Get level values using level name "Two" −print("Level values using level name...", multiIndex.get_level_values("Two"))ExampleFollowing is the code −import pandas as pd # MultiIndex is a multi-level, or hierarchical, index object for pandas objects multiIndex = pd.MultiIndex.from_arrays([list('pqrrss'), list('strvwx')], names=['One', 'Two']) # display the MultiIndex print("The MultiIndex...", multiIndex) # get the levels ... Read More
To return vector of label values using integer position of the level in the MultiIndex, use the MultiIndex.get_level_values() method in Pandas. Set the level as an argument.At first, import the required libraries −import pandas as pdMultiIndex is a multi-level, or hierarchical, index object for pandas objects −multiIndex = pd.MultiIndex.from_arrays([list('pqrrss'), list('strvwx')], names=['One', 'Two']) Display the MultiIndex −print("The MultiIndex...", multiIndex)Get level values at level 0 −print("Level values at level 0...", multiIndex.get_level_values(0)) ExampleFollowing is the code −import pandas as pd # MultiIndex is a multi-level, or hierarchical, index object for pandas objects multiIndex = pd.MultiIndex.from_arrays([list('pqrrss'), list('strvwx')], names=['One', 'Two']) # display ... Read More
To return vector of label values for requested level in a MultiIndex, use the multiIndex.get_level_values() method. Set the level name as an argument.At first, import the required libraries −import pandas as pdMultiIndex is a multi-level, or hierarchical, index object for pandas objects −multiIndex = pd.MultiIndex.from_arrays([list('pqrrss'), list('strvwx')], names=['One', 'Two'])Display the MultiIndex −print("The MultiIndex...", multiIndex) Get the levels in MultiIndex −print("The levels in MultiIndex...", multiIndex.levels)Get level values at level 0 −print("Level values...", multiIndex.get_level_values(0)) ExampleFollowing is the code −import pandas as pd # MultiIndex is a multi-level, or hierarchical, index object for pandas objects multiIndex = pd.MultiIndex.from_arrays([list('pqrrss'), list('strvwx')], names=['One', 'Two']) # ... Read More
To put xtick labels in a box, we can take the following stepsStepsCreate a new figure or activate an existing figure.Get the current axis of the figure.Set the left and bottom position of the axes.Set the position of the spines, i.e., bottom and left.To put xtick labels in a box, iterate the ticklabels and use set_bbox() method.To display the figure, use Show() method.Exampleimport matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True plt.figure() ax = plt.gca() ax.xaxis.set_ticks_position('bottom') ax.yaxis.set_ticks_position('left') ax.spines['bottom'].set_position(('data', 0)) ax.spines['left'].set_position(('data', 0)) for label in ax.get_xticklabels(): label.set_fontsize(12) label.set_bbox(dict(facecolor='red', edgecolor='black', alpha=0.7)) ... Read More
To plot a time as an index value in a Pandas dataframe in matplotlib, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a Pandas dataframe with two columns, time and speed.Set the DataFrame index using existing columns.To display the figure, use Show() method.Examplefrom 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 # Pandas dataframe df = pd.DataFrame(dict(time=list(pd.date_range("2021-01-01 12:00:00", periods=10)), speed=np.linspace(1, 10, 10))) # Set the dataframe index df.set_index('time').plot() # ... Read More
To remove the axis tick marks on a Seaborn heatmap, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create random data points with 4×4 dimension.Plot the rectangular data as a color-encoded matrix.Use tick_params() for changing the appearance of ticks and tick labels. Use left=false and bottom=false to remove the tick marks.To display the figure, use Show() method.Exampleimport numpy as np import seaborn as sns from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True data = np.random.rand(4, 4) ax = sns.heatmap(data, vmax=1) ax.tick_params(left=False, bottom=False) ... Read More
To make logically shading region for a curve in matplotlib, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create t, s1 and s2 data points using numpy.Create a figure and a set of subplots.Plot t and s1 data points; add a horizontal line across the axis.Create a collection of horizontal bars spanning *yrange* with a sequence of xranges.Add a '~.Collection' to the axes' collections; return the collection.To display the figure, use Show() method.Exampleimport numpy as np import matplotlib.pyplot as plt import matplotlib.collections as collections plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True ... Read More
To show the count values on the top of a bar in a countplot, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a Pandas dataframe with one column.A countplot can be thought of as a histogram across a categorical, instead of a quantitative, variable.Iterate the returned axes of the countplot and show the count values at the top of the bars.To display the figure, use Show() method.Exampleimport seaborn as sns import matplotlib.pyplot as plt import numpy as np import pandas as pd plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True ... Read More
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 More