Wrangling Data for Data Analysts with Python

提供方
Coursera Project Network
在此指导项目中,您将:

You will be able to query Quandl's API for dummy data, read the data from the JSON file, and calculate the maximum and the minimum price.

You will be able to calculate the biggest price change, the average of a Turnover column in a specific year based on the analysis of this data.

Clock1 hour
Beginner初级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

By the end of this project, you will be able to analyze and data and answer three different questions by Data wrangling which is the process of gathering, selecting, and transforming data to answer an analytical question using Python. In this project, you will be able to gather the data for the whole year of 2020 and query it from the Quandl website using its API. It’s a free website for dummy data. You will be able to convert the returned JSON data into a Python dictionary. And you will be able to analyze this data to calculate the highest and lowest prices in this period, the biggest change based on High and Low price during this year, And finally, the average makeover during this year. This guided project is for people in the field of business and data analysis. people who want to wrangle data and answer business questions and Clarify the use case and predict the relations between the source data. It provides you with important steps to be a data analyst. Moreover, it equips you with the knowledge in python's native data structures Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

您要培养的技能

  • Data Wrangling
  • Data Analysis
  • Python Programming
  • Application Programming Interfaces (API)

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  1. You will be able to query Quandl's API for dummy data.

  2. You will be able to read the data from JSON file and calculate the maximum and the minimum of the opening column.

  3.  You will be able to calculate the biggest price change  on any day in a specific year.

  4. You will be able to calculate the average of a Turnover column in a specific year.

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

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