Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
To set storage-indexed locations to corresponding values, use the ma.MaskedArray.put() method in Numpy. The "mode" parameter specifies how out-of-bounds indices will behave. Sets self._data.flat[n] = values[n] for each n in indices. If values is shorter than indices then it will repeat. If values has some masked values, the initial mask is updated in consequence, else the corresponding values are unmasked.The indices are the target indices, interpreted as integers. The mode specifies how out-of-bounds indices will behave. ‘raise’ : raise an error. ‘wrap’ : wrap around. ‘clip’ : clip to the range.StepsAt first, import the required library −import numpy as np ... Read More
To return a view of the MaskedArray data in Numpy, use the ma.MaskedArray.view() method.The a.view() is used two different waysa.view(some_dtype) or a.view(dtype=some_dtype) constructs a view of the array’s memory with a different data-type. This can cause a reinterpretation of the bytes of memory.a.view(ndarray_subclass) or a.view(type=ndarray_subclass) just returns an instance of ndarray_subclass that looks at the same array. This does not cause a reinterpretation of the memory.StepsAt first, import the required library −import numpy as np import numpy.ma as maCreate an array with int elements using the numpy.array() method −arr = np.array([[35, 85], [67, 33]]) print("Array...", arr) print("Array type...", arr.dtype)Get the ... Read More
To copy an element of an array to a standard Python scalar and return it, use the ma.MaskedArray.item() method in Numpy.The *args parameter, ifnone − in this case, the method only works for arrays with one element (a.size == 1), which element is copied into a standard Python scalar object and returned.int_type − this argument is interpreted as a flat index into the array, specifying which element to copy and return.tuple of int_types − functions as does a single int_type argument, except that the argument is interpreted as an nd-index into the array.StepsAt first, import the required library −import numpy ... Read More
To format a float using matplotlib's LaTeX formatter, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.Plot the x and y data points using plot() method.Fill the area between the curve.Set the title of the figure with LaTeX representation.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt # Set the figures size plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True # x and y data points x = np.linspace(-5, 5, 100) y = x**3/3 ... Read More
To set local rcParams or rcParams for one figure in matplotlib, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Initialize a variable N to store the number of sample data.Create x and y data points using numpy.Return a context manager for temporarily changing rcParams.Add a subplot to the current figure, at index 1.Plot the x and y data points, using plot() method.Add a subplot to the current figure, at index 2.Plot the x and y data points, using plot() method.To display the figure, use show() method.Exampleimport pandas as pd import ... Read More
To plot a multivariate function in Python, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Create random x, y and z data points using numpy.Create a figure and a set of subplots.Create a scatter plot with x, y and z data points.Create a colorbar for a ScalarMappable instance, s.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 def func(x, y): return 3 * x + 4 * y - 2 + np.random.randn(30) x, y ... Read More
To make a polygon radar (spider) chart in Python, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Create a Pandas dataframe with sports and values columns.Create a new figure or activate an existing figure.Add an 'ax' to the figure as part of a subplot arrangement.Based on data frame values, get the theta value.Get the values list of the data frame.Make a bar plot with theta and values data points.Fill the area between polygon.To display the figure, use show() method.Exampleimport pandas as pd import matplotlib.pyplot as plt import numpy as np ... Read More
To add a legend in a 3D scatterplot with scatter() in matplotlib, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Initialize a variable N to store the number of sample data.Create x and y data points; make z1 and z2 data points list.Add a subplot to the current figure, with projection='3d'.Plot the x, y and z1 data points using plot() points on 2d axes, with marker *.Plot the x, y and z2 data points using plot() points on 2d axes, with marker o.Place legend on the figure.To display the figure ... Read More
To remove NaN values from a dataframe without filter or interpolate, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Create an array to make a Pandas data frame.One-dimensional ndarray with axis labels (including time series).Plotting interpolation, 'index', 'values' − Use the actual numerical values of the index.To display the figure, use show() method.Exampleimport numpy as np import pandas as pd from matplotlib import pyplot as plt # Set the figure size plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True # Numpy array data = np.array([1., 1.2, 0.89, np.NAN, ... Read More
To specify different colors for different bars in a matplotlib histogram, 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.Plot a histogram with random data with 100 sample data.Iterate in the range of number of bins and set random facecolor for each bar.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt import random import string # Set the figure size plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True # Figure and set of subplots fig, ax = ... Read More