MD AFROJ ALAM Data cleaning
No reviews yet

ChatGPT

You said:
Data Cleansing Tutorial
ChatGPT said:
ChatGPT

You said:
Data Cleansing Tutorial
ChatGPT said:
ChatGPT
Data cleansing (or data cleaning) involves detecting and correcting (or removing) inaccurate records from a dataset. Below is a step-by-step tutorial on how to clean data effectively.

Step 1: Understand the Dataset
Before starting, you need to explore and understand the data. Look at the structure, types of values, and common issues like:

Missing data
Duplicates
Inconsistencies (e.g., different date formats)
Outliers
Step 2: Remove Duplicates
Duplicates can skew analysis. In Excel, to remove duplicates:

Select the data range.
Go to the Data tab.
Click Remove Duplicates and specify which columns to check for duplicates.
Step 3: Handle Missing Data
You can handle missing values by:

Removing rows: If the missing data is minimal and random.
Filling values: For example, fill missing numeric data with the mean, median, or mode.
Interpolation: Use methods to estimate missing values based on other data.
In Excel, you can use:

Go To Special: To highlight blanks, select the range, press Ctrl + G, choose Special, then select Blanks.
Formulas: Use =IF(ISBLANK(cell), replacement, cell) to fill blank cells conditionally.
Step 4: Standardize Data
Ensure uniform formatting for dates, text (e.g., all lowercase or capitalized), etc.

Text cases: Use =UPPER(), =LOWER(), or =PROPER() to standardize text.
Trim extra spaces: Use =TRIM() to remove unnecessary spaces.
Consistent formatting: For dates or currency, select the cells, right-click, choose Format Cells, and apply consistent formats.

Subjects

  • Data cleaning, visualisation, validation, mining and analysis Expert

Experience

No experience mentioned.

Education

  • Diploma (Feb, 2016–Aug, 2019) from Delhi University, New Delhi–scored 10

Fee details

    ₹1,500/hour (US$17.69/hour)

    1hour charges 1500 inr

Reviews

No reviews yet. Be the first one to review this tutor.