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1. towardsdatascience.com › exploratory-data-analysisExploratory Data Analysis With Movies | by Jeremy Lee ...

   towardsdatascience.com › exploratory-data-analysis

   Sep 6, 2020 · The math behind VAR is simple: if across all movies the average net profit is 100 dollars and the average net profit of movies from ‘Actor: X’ is 200 dollars he/she would have a VAR of 2. This number represents X times over the average. We used a minimum cutoff value of 10 movies for actors and 5 movies for directors.

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     Exploratory Data Analysis With Movies. An investigation into...

2. www.analyticsvidhya.com › blog › 2021Data Analysis Using Pandas | Guide to Pandas Data Analysis

   www.analyticsvidhya.com › blog › 2021

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   4 days ago · This makes python highly flexible and extremely useful for data cleaning and data manipulation. Pandas is highly flexible and provides functions for performing operations like merging, reshaping, joining, and concatenating data. Let’s first look at the two most used data structures provided by Pandas.

3. realpython.com › python-for-data-analysisUsing Python for Data Analysis

   realpython.com › python-for-data-analysis

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   Jan 17, 2024 · In this tutorial, you’ll use a file named james_bond_data.csv.This is a doctored version of the free James Bond Movie Dataset.The james_bond_data.csv file contains a subset of the original data with some of the records altered to make them suitable for this tutorial.

4. www.cliffsnotes.com › study-notes › 21253993Exploring Movie Box Office Records: Data Analysis Tutorial

   www.cliffsnotes.com › study-notes › 21253993

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   Sep 9, 2024 · 1 GEA1000 QUANTITATIVE REASONING WITH DATA TUTORIAL 1 Please work on the problems before coming to class. In class, you will engage in group work. In class, you will engage in group work. In this tutorial, we will be looking at two case studies: • Exploring box office records for movies • A new system of teaching mathematics Case Study 1: Exploring Box office records for movies.

5. towardsdatascience.com › a-data-scientistsA Data Scientist’s Essential Guide to Exploratory Data Analysis

   towardsdatascience.com › a-data-scientists

   May 30, 2023 · Introduction. Exploratory Data Analysis (EDA) is the single most important task to conduct at the beginning of every data science project. In essence, it involves thoroughly examining and characterizing your data in order to find its underlying characteristics, possible anomalies, and hidden patterns and relationships.

   • Author: Miriam Santos

6. www.geeksforgeeks.org › data-analysis-with-pythonData Analysis with Python - GeeksforGeeks

   www.geeksforgeeks.org › data-analysis-with-python

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   Mar 20, 2024 · Data Analysis is the technique of collecting, transforming, and organizing data to make future predictions and informed data-driven decisions. It also helps to find possible solutions for a business problem. There are six steps for Data Analysis. They are: Ask or Specify Data Requirements. Prepare or Collect Data.

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   Is data analysis just one piece of the puzzle?

   • However, data analysis is just one piece of the puzzle. There’s so much more to learn before you can break into data science. Whenever you’re ready for the next step, the 365 Data Science Program offers you self-paced courses led by renowned industry experts.

   A Beginner’s Guide to Data Analysis in Python - 365 Data Science

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   What is a data analysis workflow?

   • A data analysis workflow is a process that provides a set of steps for your analysis team to follow when analyzing data. The implementation of each of these steps will vary depending on the nature of your analysis, but following an agreed-upon workflow allows everyone involved to know what needs to happen and to see how the project is progressing.

   Using Python for Data Analysis

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   What are best practices in data analysis?

   • Best practices therefore call for the thorough investigation of individual properties such as descriptive statistics and data distribution. These will highlight the need for subsequent tasks of outlier removal, standardization, label encoding, data imputation, data augmentation, and other types of preprocessing.

   A Data Scientist’s Essential Guide to Exploratory Data Analysis

   towardsdatascience.com/a-data-scientists-essential-guide-to-exploratory-data-analysis-25637eee0cf6

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8. 365datascience.com › tutorials › python-tutorialsA Beginner’s Guide to Data Analysis in Python

   365datascience.com › tutorials › python-tutorials

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   Apr 21, 2023 · A Beginner’s Guide to Data Analysis in Python. Join over 2 million students who advanced their careers with 365 Data Science. Learn from instructors who have worked at Meta, Spotify, Google, IKEA, Netflix, and Coca-Cola and master Python, SQL, Excel, machine learning, data analysis, AI fundamentals, and more. Start for Free.