Pandas is a Python library used for data manipulation and analysis. It introduces two main data structures: Series and DataFrame. Series is a one-dimensional array-like object containing data and labels, while DataFrame is a spreadsheet-like structure containing an ordered collection of columns. NumPy must be installed before Pandas, SciPy, or other Python packages for scientific computing. These packages provide powerful tools for data analysis and visualization.

1. DATA ANALYSIS PACKAGES

3. DATA ANALYSIS USING PYTHON
Pandas is a software library used in Python programming languages for data manipulation and
analysis.
Pandas is well suited for many different kinds of data:
● Tabular data with heterogeneously-typed columns.
● Ordered and unordered time series data.
● Arbitrary matrix data with row and column labels.
● Any other form of observational/statistical data sets.
The data actually need not be labeled at all to be
placed into a pandas data structure.

4. PANDAS OPERATIONS
OPERATIONS
Slicing the
dataframe
Joining and merging
ConcatenationChanging the index
Joining and mergingData conversation

5. PANDAS DATA STRUCTURES
Pandas introduces two new data structures to Python :
 Series
 DataFrame

6. PANDAS-DATA STRUCTURES: SERIES
 One-dimensional array-like object
containing data and labels (or
index)
 Lots of ways to build a Series

7. SERIES - WORKING WITH THE INDEX
 A series index can be specified
 Single values can be selected by index
 Multiple values can be selected with
multiple indexes

8. SERIES - WORKING WITH THE INDEX
 Think of a Series as a fixed-length, order
dict
 However, unlike dict,index items don't
have to be unique

9. SERIES - OPERATIONS
 Filtering
 NumPy-type operations on data

10. SERIES - INCOMPLETE DATA
Pandas can accommodate incomplete
data

11. SERIES- AUTOMATIC ALIGNMENT
Unlike in NumPy ndarray, data is
automatically aligned.

12. DATA STRUCTURES : DATAFRAME
 Spreadsheet-like data structure containing an order collection of columns
 Has both a row and column index
 Consider as dict of Series (with shared index)

13. DATAFRAME
Creation with dictionary of equal-length lists

14. DATAFRAME
Creation with dictionary of dictionary

15. DATAFRAME
 Columns can be retrieved as Series:
dict notation
attribute notation
 Rows can retrieved by position or by
name (using ix attribute)

16. DATAFRAME
New Columns can be added (by
computation or direct assignment)

17. DATAFRAME - REINDEXING
Creation of new object with the data
conformed to a new index

18. INSTALLATION OF PANDAS
To install pandas module in terminal write: Sudo apt-get install python-pandas

19. PANDAS
Pandas is an open source Python library for data analysis.
Pandas Python is one of those libraries for data analysis, that contains high-level data structures and tools to
help data scientists or data analysts manipulate data in a very simple and easy way.

20. NUMPY
Numpy is the standard package for scientific and numerical computing in python:
 Powerful N-dimensional array object.
 sophisticated (broadcasting) functions.
 Tools for integrating C/C++ and Fortran code.
 Useful linear algebra,Fourier transform and random number capabilities.
 Numpy provides the data structure.
 NumPy has to be installed first and then any other add-ons can be installed.

21. INSTALLATION OF NUMPY
To install numpy module in terminal write: Sudo apt-get install python-numpy

22. SCIPY
Scientific Python code name, SciPy-It is an assortment of mathematical functions and algorithms
which are built on top of Python’s extension NumPy.
 Scipy depends on Numpy’s data structure.
 SciPy is useful for data-processing and prototyping of systems.
 SciPy provides various high-level commands and classes for manipulating and visualizing
data.
 Scipy provides the application layer.

23. INSTALLATION OF SCIPY
To install Scipy module in terminal write: Sudo apt-get install python-scipy

24. MATPLOTLIB
 Matlplotlib is a Python module for visualization.
 Matplotlib allows you to easily make line graphs, pie chart, histogram and other professional
grade figures.
 Using Matplotlib you can customize every aspect of a figure.
 When used within IPython, Matplotlib has interactive features like zooming and panning.
 It supports different GUI back ends on all operating systems, and can also export graphics to
common vector and graphics formats: PDF, SVG, JPG, PNG, BMP, GIF, etc.
 Matplotlib tries to make easy things easy and hard things possible.

25. INSTALLATION OF MATPLOTLIB
To install Matplotlib module in terminal write: Sudo apt-get install python-matplotlib

26.  Sci-Kit learn are modules or plugins for Scipy,they are too specialized to be included in
SciPy itself.
 Sci-Kit Learn is built upon SciPy and thus to use Sci-Kit Learn it is necessary to install various
other Python libraries – Pandas, NumPy, SciPy and IPython.
 Scikit-learn helps to quickly implement popular algorithms on your dataset.
 Scikit-learn includes tools for many standard machine-learning tasks.
SCI-KIT LEARN

27. INSTALLATION OF SCI-KIT LEARN
If you already have a working installation of numpy and scipy, the easiest way to install scikit-learn is using pip:
pip install -U scikit-learn