Course |
Project |
Description |
Data Analysis with Python
Skills: read data from sources like CSVs and SQL, and use libraries like Numpy, Pandas, Matplotlib, and Seaborn to process and visualize data.
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Mean-Variance-Standard Deviation Calculator
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Use Numpy to output the mean, variance, standard deviation, max, min, and sum of the rows, columns, and elements in a 3 x 3 matrix. Input will be a list of 9 integers and raises error if list has less than 9 integers.
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Demographic Data Analyzer
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Analyze demographic data using Pandas. You are given a dataset of demographic data that was extracted from the 1994 Census database.
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Medical Data Visualizer
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Use pandas, matplotlib, and seaborn libraries to explore the relationship between cardiac disease, body measurements, blood markers, and lifestyle choices.
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Page View Time Series Visualizer
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Visualize time series data using a line chart, bar chart, and box plots. You will use Pandas, Matplotlib, and Seaborn to visualize a dataset containing the number of page views each day.
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Sea Level Predictor
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Analyze a dataset of the global average sea level change since 1880. You will use the data to predict the sea level change through year 2050.
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