Data analysis with Python - Importing dataset

Data analysis with Python by IBM 시리즈 - 1강 Importing dataset

 

• Python packages for Data Science

1. Scientifics computing: Pandas / Numpy / SciPy
2. Visualization: Matplotlib / Seaborn
3. 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