When you enable the‘inline’matplotlib backend, the output of the plotting commands written will be displayed inline within the frontends likejupyter notebook. It means, the plot/graph will be displayed directly below the cell (where the plotting commands are written) and the resulted plot/graph...
They act as inline comments, eliminating the need for separate comments to describe the function or variable’s purpose. Collaboration: Collaboration is facilitated by uniform naming conventions and useful identifiers while working on projects with several developers. The codebase’s functions and ...
import numpy as np # Some visualization libraries from matplotlib import pyplot as plt import seaborn as sns ## Some other snippit of codes to get the setting right ## This is so that the chart created by matplotlib can be shown in the jupyter notebook. %matplotlib inline %config InlineBa...
# Import all libraries for this portion of the blog post from scipy.integrate import quad import numpy as np import matplotlib.pyplot as plt %matplotlib inline x = np.linspace(-4, 4, num = 100) constant = 1.0 / np.sqrt(2*np.pi) pdf_normal_distribution = constant * np.exp((-x**...
%matplotlib inline import matplotlib.pyplot as plt from matplotlib import style style.use('ggplot') import numpy as np class SVM(object): def __init__(self,visualization=True): self.visualization = visualization self.colors = {1:'r',-1:'b'} if self.visualization: self.fig...
#importing packages %matplotlib inline import scipy.stats as stats import numpy as np import pandas as pd import matplotlib.pyplot as plt import seaborn as sns plt.style.use('ggplot') df = pd.read_csv('creditcard.csv')We can use different algorithms to get the results. But which one to...
Visualizations.Graphics and charts can be generated from code, by way of modules likeMatplotlib,Plotly, orBokeh. Like output, these visualizations appear inline next to the code that generates them. However, code can also be configured to write them out to external files if needed. ...
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Hello Lakshay, amazing article, but please do add this line in the import section: from pyod.models.lof import LOF also these modifie lines X1 = df['Item_MRP'].values.reshape(-1,1) X2 = df['Item_Outlet_Sales'].values.reshape(-1,1) Thanks again ...