How to deal with index with iloc and loc in DataFrames Pandas | 1.7.3 Analysis Data science Python

Do you understand the differences between iloc and loc??

In this chapter of the video series DataFrames in the tutorial course in statistics and data science with Python we will see the multiple ways to explore Data Frames with python using iloc, loc, at and iat.

- 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

- What is a Data Frame?
- EXCEL table or Sql Table?
- DataFrame constructor and its options
- Using pandas as pd
- Defining a data frame with lists
- Defining a data frame with dictionary
- Defining a data frame with tuples and lists
- Defining data frames with series

- 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?

Any comments or suggestions are welcome.

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Intro data manipulation with Pandas in Python: remove drop groupby plot | Data science Tutorial