Notice
Recent Posts
Recent Comments
Link
| 일 | 월 | 화 | 수 | 목 | 금 | 토 |
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 6 | 7 | 8 | 9 | 10 | 11 | 12 |
| 13 | 14 | 15 | 16 | 17 | 18 | 19 |
| 20 | 21 | 22 | 23 | 24 | 25 | 26 |
| 27 | 28 | 29 | 30 | 31 |
Tags
- matplotlib.pyplot
- variables
- __init__
- matplotlib
- Default X points
- train/test
- AS
- pie charts
- Text mining
- data distribution
- PANDAS
- continue
- start exercise
- PROJECT
- Python
- break
- Else
- Github
- iterates
- multiple lines
- line color
- polynomial regression
- MySQL
- error
- Text Analytics
- SQL
- line width
- machine learning
- For loops
- self parameter
Archives
- Today
- Total
목록Cleaning data (1)
Data Science Explorer
Pandas: Cleaning Data of Wrong Format
Sometimes our data might not be in the format we expect. For example, numbers might be stored as text, or dates might not be recognized as dates. We need to identify these issues. Convert into a Correct Format Example Convert the 'Age' column to numbers. df['Age'] = pd.to_numeric (df['Age'], errors = 'coerce') ** The 'errors' parameter helps handle cases where the conversion isn't possible, and ..
Python
2023. 10. 29. 10:37