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You should always remember that if you want to sort the values in descending order, then you should assign
False value to the parameter ‘ascending’. For example,

df = pd.read_excel(r’F:\Book_list.xlsx’)
df = df.sort_values(by=’Price’,ascending = False)
print (df.head())
This code sorts the list of items in descending order on the basis of price. Thus, you will get the following output:

Matplotlib
Matplotlib is one of the most popular Python packages used for data visualization.
It has a platform independent library for making 2D plots from data in arrays.
Matplotlib is written in Python and makes use of NumPy, the numerical
mathematics extension of Python.

Using Matplotlib, we can draw various types of charts and graphs. The data visualisation in the form of charts
and graphs helps us to make a thought of clarity about trends and patterns. In simple terms, we can say that data
visualisation is a good technique for reasoning about quantitative information. Here, some types of graphs are
given below that we can draw with this package:

u Pie Plot u Area Plot u Bar Graph u Scatter Plot u Histogram

Using this package, we can easily customize all kinds of graphical properties, like controlling the width and
colour of lines, annotating, or adding a legend etc. As you know, we have a lot of datasets at the time of data
acquisition. The appropriate exploration of datasets is a necessary step before training an AI model.
With the help of these packages, we can easily explore the meaningful data.

STATISTICAL LEARNING WITH PYTHON

The term “Data science” is an interdisciplinary field that uses scientific methods, processes, algorithms and
systems to extract knowledge and insights among the data. The field of data science is purely based on
mathematics and statistics because we cannot train a model until appropriate analysis of data takes place.

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