Data Analyst Duo is an instagram community (@𝒅𝒂𝒕𝒂𝒂𝒏𝒂𝒍𝒚𝒔𝒕𝒅𝒖𝒐) of ~𝟕𝟓𝐤 data enthusiasts founded by two individuals Aditi & Kalpesh. They share content around statistics, data science & analytics with budding data aspirants. Domain: Social Media
Data: dataanalystduo instagram analytics.xlsx- : The data set contains stats about the channel (@𝒅𝒂𝒕𝒂𝒂𝒏𝒂𝒍𝒚𝒔𝒕𝒅𝒖𝒐)
Data Dictionary:
- Date: Date
- Instagram reach: The number of unique accounts that saw any of your posts or stories at least once. Reach is different from impressions, which may include multiple views of your posts by the same accounts. This metric is estimated.
- Instagram profile visits: The number of times your profile was visited.
- New Instagram followers: The number of new accounts that started following your Instagram account.
- Title: Title of the post
- Post type: Type of post - IG video, IG carousel, IG Image
- Impressions: The number of times your post was viewed
- Reach: The number of accounts your post was reached
- Shares: The number of times you post was shared
- Follows: The number of new accounts that started following your Instagram account.
- Likes: The number of likes on the post
- Comments: The number of comments on the post
- Saves: The number of saves on the post
The goal is to analyse the data and provide recommendations on what type of post are working for the page.
Note
- Unauthorised use or distribution of this project prohibited @dataanalystduo
- Dataset is owned by @dataanalystduo page & instagram.
- Data cleaning is the process of identifying and correcting or removing errors, inconsistencies, and inaccuracies in a dataset.
- Observation writing involves examining the data and noting any notable findings, anomalies, or areas of interest.
- Exploratory Data Analysis (EDA) is the process of examining and visualizing a dataset to understand its main characteristics, such as the distribution of data, the relationships between variables, and any anomalies or patterns that may exist. The goal of EDA is to uncover insights and trends that can help inform further analysis or decision-making. It is often the first step in any data analysis project, as it provides a foundation for more advanced statistical methods and models.