Converting data type to Numbers in Python
📊 *Data Cleaning Tip: Converting Data to Numbers in Python*
Sometimes a column that looks like numbers is actually stored as text. When this happens, calculations, summaries, and visualizations may not work correctly.
In this video, you'll learn how to convert a column from text (**string**) to a numeric data type using Pandas.
🎯 Why is this important?
❌ You can't calculate averages on text data
❌ You can't perform mathematical operations correctly
❌ Your analysis may produce errors
✅ Convert text to numbers and unlock the full power of your data!
Example:
```python
df['sales'] = pd.to_numeric(df['sales'])
```
Or:
```python
df['age'] = df['age'].astype(int)
```
After conversion, you'll be able to:
📈 Calculate statistics
📊 Create visualizations
🔍 Perform accurate analysis
Small data cleaning steps like this make a big difference in the quality of your results.
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