text: df = spark.range(1000).toDF("number")
  display(df)
  
  df.describe().show()
  
  df["number"]
  
  df.columns
  
  df.schema
  
  df.select("number").show(15)
  
  df.where("number > 10 and number < 14").show()
  
  seed = 10
  withReplacement = False
  fraction = 0.02
  df.sample(withReplacement, fraction, seed).show(100)
  
  pdf = df.toPandas()
  pdf.dtypes
  
  import pandas as pd
  import numpy as  np
  pdf = pd.DataFrame(data={'ColumnA':np.linspace(0, 1, 11),
                          'ColumnB':['red', 'yellow','blue', 'green', 'red', \
                                     'green','green','red', 'yellow','blue', 'green'],
                          'ColumnC': np.random.randint(11)}) 
  pdf
  
  #One column
  pdf['ColumnA']
  
  #Single value
  pdf.loc[0, 'ColumnA']
  
  #Slicing by index
  pdf.loc[3:7:2]
  
  pdf['ColumnB']=='red'
  
  #Boolean mask
  pdf[pdf['ColumnB']=='red']
  
  #Boolean mask multiple conditions
  pdf[(pdf['ColumnB']=='red') & (pdf['ColumnA']==0.4)]
  
  