Agile Data Science - Working with Reports



In this section, we will understand about report creation, which is an significant module of agile methodology. Agile sprints chart pages created by visualization into full-blown reports. With reports, charts become intelligent, static pages become dynamic and network related data. The characteristics of reports phase of the data value pyramid is shown below −

The-Data-Value-Prramid-Reports

We will lay more stress on creating csv file, which can be utilized as report for data science analysis, and drawing conclusion. Although agile focusses on less documentation, generating reports to mention the progress of product development is always considered.

import csv
#----------------------------------------------------------------------
def csv_writer(data, path):
   """
      Write data to a CSV file path
   """
   with open(path, "wb") as csv_file:
   writer = csv.writer(csv_file, delimiter=',')
   for line in data:
   writer.writerow(line)
#----------------------------------------------------------------------
if __name__ == "__main__":
   data = ["first_name,last_name,city".split(","),
      "Tyrese,Hirthe,Strackeport".split(","),
      "Jules,Dicki,Lake Nickolasville".split(","),
      "Dedric,Medhurst,Stiedemannberg".split(",")
   ]
	
   path = "output.csv"
   csv_writer(data, path)

The above code will assist you generate the “csv file” as shown below −

comma_separated_values

Let us consider the following benefits of csv (comma- separated values) reports −

  • It is human friendly and simple to edit manually.
  • It is easy to implement and parse.
  • CSV can be handled in all applications.
  • It is littler and faster to handle.
  • CSV follows a standard format.
  • It gives straightforward schema for data researchers.




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