• Installing the Anaconda Navigator
• Launching the Jupyter Notebook
• Input modes
• Spelling of Python code
• Writing out, showing data
• The correct spelling of folders, file paths
• Accessing folder contents – The OS module
• Floor division, remainder
• Exponentiation, roots
• Main data types of variables

• Converting to uppercase, lowercase
• Removing unnecessary spaces
• Replacing string parts
• Searching for text (contains)
• Searching for text (starts or ends with)
• Slicing strings (left, middle, right)
• Splitting texts
• Concatenating texts
• Formatting strings with curly braces

• The Pandas library
• Base data of folders and files
• Reading CSV files into Dataframes
• Data about the Dataframe
• Capitalize each word in Dataframe column
• Trim leading and trailing spaces in column
• Replace texts in column
• Splitting text to columns
• Merging columns
• Changing column data types
• Deleting columns and rows
• Renaming columns
• Reordering column sequence
• Adding new columns
• Sorting rows
• Exporting data to CSV files
• Creating a Markdown
• Tasks can be organized to separate programs
• Running other Python programs 1.
• Running other Python programs 2.
• Resetting the index
• Slicing, filtering the Dataframe 1.
• Slicing, filtering the Dataframe 2.
• Removing duplicates
• Inserting a new ID index column
• Quickly replacing texts in Python code
• Exporting data to new Excel file
• Exporting data to existing Excel file
• Reading data from SQL database

• Useful keyboard shortcuts – in any mode
• Useful keyboard shortcuts – in Edit mode
• Useful keyboard shortcuts – in Command mode
• Handling dates
• Catching errors (TRY – EXCEPT)
• Asking the user to input data (INPUT)
• Creating and deleting folders in file system
• Deleting files from file system
• Notifications with beeping sound

• Defining custom functions (def)
• Measuring runtime
• Custom LAMBDA functions
• Rounding numbers

• Conditional (IF)
• Searching for texts with IF
• Binary variables (True or False)
• Loops (FOR)
• Loops (WHILE)
• Looping through files in a folder
• Appending multiple files into one Dataframe
• Creating dimension tables from multiple files

• Creating Lists
• Adding, modifying, deleting List items
• Looping through List elements
• Specific elements in a List
• Splitting texts to List
• Concatenating texts from a List
• Removing non-numeric items from List
• Finding the difference between Lists
• Deleting variables, Lists, etc. from memory

• Simplifying our code with Lists
• Reading data from Excel files into a Dataframe
• Delete rows or columns with empty values
• Handling columns with the same header
• Filtering Dataframe columns based on text
• Adding column or row values to List
• Filtering Dataframe columns with a List
• Merging two Dataframes to look up values
• Reading CSV files with special parameters
• Reading large size CSV files (millions of rows)

• Creating a Dictionary
• Looping through a Dictionary
• Pairing Lists into a Dictionary
• Removing duplicates from Lists with Dictionary

• Renaming Dataframe columns or data with Dictionary
• Looping through columns
• Looping through rows
• Looping through certain files
• Creating template programs
• Calculating with column values
• Missing (blank) values in columns
• Aggregating column values (sum, average etc.)
• Aggregating row values
• Add ranges for values
• Aggregation by groups – Pivot table
• Creating charts
• Finding differences between tables
• The last row index in an Excel table
• Writing to Excel files’ specific cells

• Module overview
• SQL basics
• Python API
• Create an AWS account
• VsCode’s Jupyter notebook vs. „simple” Jupyter notebook

• Get playslist data
• How to read the JSON api response

• Which columns are we using?
• Create the dataframes
• S3

• Lambda
• Create the first lambda function (extract)
• Create the second lambda function (transform)

• Glue
• Athena
• Create visualisations

Vizsgafeladat