From the course: Complete Guide to Generative AI for Data Analysis and Data Science
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Solution: Visualizing data
From the course: Complete Guide to Generative AI for Data Analysis and Data Science
Solution: Visualizing data
(bright upbeat music) - [Instructor] Let's see the solution to this challenge regarding visualization. The first thing I want to do is attach the dataset that is available with this lesson. I have already downloaded it to my computer, so I'm going to upload it into ChatGPT. And for this lesson, I'm going to go over here and I'm going to grab the grocery sales dataset for this chapter. And the prompt that we're going to use is the following, create a Python script to generate a visualization to show the distribution of data in the cost per unit column and sales price per unit column. So again, we're almost literally taking our requirement and using it as a prompt where there's very little tweaking that we need to do. And what we see here is, of course, display of the data with the date sold, product name, product category, and then the cost, and sale information, and unit sold information, so let's see what kind of script is being generated. And what we see here, the script shows us…
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Contents
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Distributions of data7m 27s
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Visualizing a normal distribution in a spreadsheet3m 29s
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Jupyter Notebook and Colab3m 51s
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Generating a normal distribution6m 23s
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Visualizing a normal distribution in Python4m 56s
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Visualizing a uniform distribution in Python3m
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Visualizing a bimodal distribution in Python5m 54s
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Challenge: Distributions of data40s
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Solution: Distribution of data4m 7s
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Inferential statistics4m 25s
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Hypothesis testing methodology4m 17s
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Analyzing customer preferences11m 20s
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Type I and type II errors1m 30s
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ANOVA tests for comparing means1m 55s
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Generating Python scripts for ANOVA3m 45s
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Testing independence of categorical variables1m 53s
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Generating Python Scripts for Chi-squared tests3m 33s
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Correlation analysis7m 12s
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Testing for normality2m 25s
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Generating Python for testing normality3m 46s
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Generating Python for correlation analysis2m 12s
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Challenge: Making inferences from data24s
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Solution: Making inferences from data3m 17s
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Linear regression7m 44s
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Evaluating linear regression models2m 37s
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Visualizing sales data1m 56s
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Building a linear regression model4m 16s
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Evaluating a sales linear regression model2m 46s
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Challenge: Building a regression model48s
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Solution: Building a regression model4m 32s
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Data files4m 9s
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Using spreadsheets with CSV files2m 43s
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Reviewing an example JSON file4m 29s
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Using jq with JSON files6m 23s
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Generating jq commands using AI6m 1s
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Dataframes in Python8m 20s
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Loading CSV data into dataframes3m 44s
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Loading JSON into dataframes6m 17s
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Inspecting dataframes4m 12s
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Data quality and data cleansing6m 28s
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Using AI for data quality and data cleansing5m 6s
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Challenge: Missing data35s
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Solution: Missing data4m
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Relational databases15m 15s
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NoSQL databases10m 21s
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Extraction, transformation, and loading data into databases5m 46s
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Introduction to SQL5m 45s
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Creating tables and inserting data8m 2s
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Querying data with SQL10m 28s
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Joining data with SQL6m 57s
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Descriptiive statistics in SQL4m 55s
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Generating synthetic data sets for a relational database7m 12s
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Generating a star schema, synthetic data, and queries3m 41s
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Challenge: Generate a relational data model1m 12s
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Solution: Generate a relational data model4m 32s
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Simple classification model8m 34s
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Handling missing data5m
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Comparing multiple algorithms6m 43s
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Classification with neural networks14m 22s
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Hyperparameter tuning6m 32s
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Evaluating feature importance2m 24s
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Challenge: Predicting consumer intent41s
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Solution: Predicting consumer intent7m 26s
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Introduction to graph theory5m 54s
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NetworkX4m 27s
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Analyzing a social network7m 15s
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Supply chains and network analysis3m 20s
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Generating a synthetic supply chain4m 5s
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Visualizing a complex supply chain3m 37s
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Finding highest betweenness scores4m 36s
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Advanced topics in supply chain analysis6m 26s
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Challenge: Analyzing a social network19s
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Solution: Analyzing a social network2m 35s
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Introduction to simulations2m 42s
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Types of simulations10m 3s
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Modeling inventory management7m 13s
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Agent-based modeling9m 43s
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Modeling the spread of infectious diseases4m 29s
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Agent-base infectious diseases modeling5m 21s
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Challenge: Simulating forest fires55s
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Solution: Simulating forest fires5m 49s
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