Learn Pandas → What is Pandas? - Business Management International Institute

Curriculum

15 Sections
47 Lessons
10 Weeks

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Pandas Introduction
Pandas is a Python library used for working with data sets. It has functions for analyzing, cleaning, exploring, and manipulating data. The name "Pandas" has a reference to both "Panel Data", and "Python Data Analysis" and was created by Wes McKinney in 2008.
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Pandas Getting Started
If you have Python and PIP already installed on a system, then installation of Pandas is very easy.
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Pandas Series
A Pandas Series is like a column in a table. It is a one-dimensional array holding data of any type.
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Pandas DataFrames
A Pandas DataFrame is a 2 dimensional data structure, like a 2 dimensional array, or a table with rows and columns.
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Pandas Read CSV
A simple way to store big data sets is to use CSV files (comma separated files). CSV files contains plain text and is a well know format that can be read by everyone including Pandas.
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- 1.1
  Read CSV Files
- 1.2
  max_rows
Pandas Read JSON
Big data sets are often stored, or extracted as JSON. JSON is plain text, but has the format of an object, and is well known in the world of programming, including Pandas.
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- 1.1
  Read JSON
- 1.2
  Dictionary as JSON
Pandas - Analyzing DataFrames
One of the most used method for getting a quick overview of the DataFrame, is the head() method. The head() method returns the headers and a specified number of rows, starting from the top.
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Pandas - Cleaning Data
Data cleaning means fixing bad data in your data set. Bad data could be: Empty cells Data in wrong format Wrong data Duplicates
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- 1.1
  Data Cleaning
- 1.2
  Our Data Set
Pandas - Cleaning Empty Cells
Empty cells can potentially give you a wrong result when you analyze data.
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Replace Empty Values
Cells with data of wrong format can make it difficult, or even impossible, to analyze data. To fix it, you have two options: remove the rows, or convert all cells in the columns into the same format
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Pandas - Cleaning Data of Wrong Format
Cells with data of wrong format can make it difficult, or even impossible, to analyze data. To fix it, you have two options: remove the rows, or convert all cells in the columns into the same format.
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Pandas - Fixing Wrong Data
Wrong data" does not have to be "empty cells" or "wrong format", it can just be wrong, like if someone registered "199" instead of "1.99". Sometimes you can spot wrong data by looking at the data set, because you have an expectation of what it should be.
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Pandas - Removing Duplicates
Duplicate rows are rows that have been registered more than one time.
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- 1.1
  Discovering Duplicates
- 1.2
  Removing Duplicates
Pandas - Data Correlations
A great aspect of the Pandas module is the corr() method. The corr() method calculates the relationship between each column in your data set.
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Pandas - Plotting
andas uses the plot() method to create diagrams. We can use Pyplot, a submodule of the Matplotlib library to visualize the diagram on the screen
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