π Exciting Internship Project at Oasis Infobyte π
I'm thrilled to share that I've just completed my 3rd task as an internship at Oasis Infobyte, and it has been an incredible learning experience! π
π Project Name :-----
Cleaning Data
π Linkedin Project Link :-----
π Dataset Link :-----
π Objective:-----
Data cleaning is the process of fixing or removing incorrect, corrupted, duplicate, or incomplete
data within a dataset. Messy data leads to unreliable outcomes. Cleaning data is an essential
part of data analysis, and demonstrating your data cleaning skills is key to landing a job. Here
are some projects to test out your data cleaning skills:
π οΈ Tools Used:-----
Python, Pandas , Matplotlib , Seaborn
Key Aspects of the Project:-----
- Data Integrity:
Ensuring the accuracy, consistency, and reliability of data throughout the
cleaning process.
- Missing Data Handling:
Dealing with missing values by either imputing them or making
informed decisions on how to handle gaps in the dataset.
Duplicate Removal: Identifying and eliminating duplicate records to maintain data uniqueness.
- Standardization:
Consistent formatting and units across the dataset for accurate analysis.
- Outlier Detection:
Identifying and addressing outliers that may skew analysis or model
performance.
I am immensely grateful to Oasis Infobyte for this opportunity. This project has not only strengthened my analytical skills but also my proficiency in Python and python Libraries . Looking forward to the next challenge!
Feel free to connect with me to discuss data analytics, Power BI, Python or any exciting opportunities! π
Contact and Feedback:
I'm always eager to share this types of post with fellow data enthusiasts . Feel free to reach out on LinkedIn or Instagram and follow me
GitHub : https://lnkd.in/dpcQSND4
LinkedIn : https://lnkd.in/dzPjc_8N
Instagram : https://lnkd.in/dr_SfWi7
Gmail : [email protected]
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