Final Exam: Prompt Engineering for Data Science

WHAT YOU WILL LEARN

• 

  Provide an overview of data analysis and visualization
  

  set up pandas
  

  import pandas
  

  import and set up pandas
  

  select specific rows and columns from a dataframe
  

  use the pd.to_datetime() function in pandas
  

  index and filter series
  

  explore pandas dataframes
  

  perform dataframe indexing
  

  implement dataframe indexing
  

  view dataframe properties and features
  

  view dataframe features and properties
  

  explore dataframe properties and features
  

  install pandas
  

  use pandas
  

  read csv files into pandas dataframes
  

  read data from a variety of sources
  

  write data out to files
  

  drop and select columns from dataframes
  

  select and drop columns from dataframes
  

  perform operations on dataframes
  

  sort dataframes
  

  iterate over and sort dataframes
  

  debug issues with sorting dataframes
  

  compute new columns in a dataframes
  

  compute new columns in dataframes
  

  use the apply and filter functions
  

  implement the apply and filter functions
  

  generate code with chain-of-thought prompting
  

  produce code with chain-of-thought prompting
• 

  perform filtering by column headers and row labels
  

  perform filtering and querying
  

  execute complex queries
  

  perform filtering with dates and strings
  

  perform simple aggregations
  

  perform groupby and aggregations
  

  remove duplicate records
  

  perform multi-column groupby
  

  clean categorical data
  

  fill missing values
  

  view and fill missing values
  

  create pivot tables
  

  generate pivot tables
  

  reshape data using pivot tables
  

  reform data using pivot tables
  

  debug issues related to pd.concat
  

  perform inner joins
  

  explore other types of joins
  

  visualize time series data
  

  perform a join on multiple columns
  

  group and aggregate time series data
  

  aggregate time series data
  

  visualize univariate data
  

  describe bivariate visualizations
  

  review bivariate visualizations
  

  explore bivariate visualizations
  

  use plotly to create interactive time series visuals
  

  create interactive time series visuals with plotly
  

  create interactive scatter charts and heatmaps
  

  create interactive heatmaps and scatter charts