Extract Year Month Day from date type variable with Pandas DataFrames | Python Data science Tutorial

Do you know the multiples ways to extract valuable information from date type variables with pandas?

In this chapter of the video series DataFrames in the tutorial course in statistics and data science with Python we will discuss the multiple ways to get year, month and more with python using Pandas.

- Create dataframes with indices and understand how index works
- New observations with new index
- Set index to a dataframe
- Using and applying reset_index
- Two columns as new indices
- Using iloc and loc with index
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- Applying the function filter for dataframes
- Using iloc and loc for filtering
- Utilizing the function where
- Condition or conditions for filtering data

- What is a Data Frame?
- EXCEL table or Sql Table?
- DataFrame constructor and its options
- Using pandas to define data frames with series
- Defining a data frame with list, dictionary, tuples and list

- How to create a dataframe with dictionaries
- Using the function describe to obtain a summary
- utilize the function shape to obtaing number of rows and columns
- What is index and how to get the indices
- Extract different values from the dataset
- What is the function head? and what is tail? size ?
- First observations in a data frame
- How to access to columns using names and brackets [ ]
- What is data type? dtype?

- Defining a dataframe and understanding its indices
- How to use iloc an loc
- Row names, column names and index number
- How to use at and iat
- Using [ ], and multiple observations
- Defining a dataframe with indices names

- Define and build dataframes from scratch
- Using assign for inserting new rows / observations
- Concatenate two dataframes into a new one
- Utilize loc and iloc
- Understanding index

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