Using pandas

• Data structures: Data Frame (i.e., table), and Series (a sequence of data, i.e., list)
• Create a data frame or series,

  import pandas as pd
  fruits = pd.DataFrame({'Apples':[30, 32], 'Bananas':[21, 22]}, index=["2018", "2019"])
  fruits
  apples = pd.Series([30, 32], index=["2018", "2019"], name="apples")
  

• Read from a file

  #read csv
  wine_reviews = pd.read_csv("../input/wine-reviews/winemag-data-130k-v2.csv")
  #examine first five rows
  wine_reviews.head()
  #check the size
  wine_reviews.shape
  

• Read from a URL

  import pandas as pd
  import requests
  import io
  #this file has no header
  url="https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data"
  s=requests.get(url).content
  c=pd.read_csv(io.StringIO(s.decode('utf-8')), header=None, names=["SepalLengthCm","SepalWidthCm","PetalLengthCm","PetalWidthCm","Species"])
  

• Accessing (dot notation & indexing as in Python dict/list operations)