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Data analysis with Python - Importing datasetData Science 2022. 8. 13. 17:12
Data analysis with Python by IBM 시리즈 - 1강 Importing dataset
- Python packages for Data Science
- Scientifics computing: Pandas / Numpy / SciPy
- Visualization: Matplotlib / Seaborn
- Algorithmic libraries(Linear Regresion등에 쓰임): Scikit-learn(머신러닝 라이브러리) / Statsmodels(Estimate statistical models, perform statistical test)
- Datatype 비교: Pandas vs Python
- dataframe.describe() 은 숫자가 아닌 columns은 생략한다. 때문에 string type column을 확인하고 싶다면
dataframe.describe(include=['object'])
혹은 데이터타입 전부를 확인하고 싶다면
df.describe(include = 'all')
- Top 30 rows and bottom 30 rows of dataframe 확인하는 법
df.info()
- Python DB-API의 두가지 concept: Connection object, Cursor object
- Connection object: Database connection, manage transactions 에 주로 쓰임
- Cursor objects: Database queries에 주로 쓰임
- 주로 쓰이는 Connection methods
cursor() # returns a new corsor object using connection commit() # commit any pending transaction to the database rollback() # causes the database to roll back to the start of any pending transaction close() # to close a database connection
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