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Python Business Intelligence Cookbook
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Data quality is a fundamental issue for business intelligence. The reliability of your analysis and, by extension, the decisions you make based on that analysis, depend on the quality of data you use.
A data quality report provides objective measures of the quality of your data making it a critical first step of the business intelligence process.
For creating our report, we are going to create a number of DataFrames from our dataset, and then merge them together at the end. The parts of our report will include the following:
Available columns
For each column:
Data type
Count of missing values
Count of present values
Number of unique values
Minimum value
Maximum value
To create your data quality report, start by importing the libraries that you need:
import pandas as pd
Next, import the data from the source CSV file using the Create a Pandas DataFrame From a CSV File recipe:
accidents_data_file = '/Users/robertdempsey/Dropbox/private/Python Business...
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