typeof() and class() functions
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infile<-'http://datayyy.com/data_R/adult.rda'
a<-load(url(infile))

> infile<-'http://datayyy.com/data_R/adult.rda'
> a<-load(url(infile))
> a
[1] "adultTrain" "adultTest" 

> typeof(adultTrain)  # [1] "list"
> class(adultTrain)   # [1] "data.frame"

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Data frame columns
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Data Frame Columns:
Explanation: Accessing columns in a data frame.
Example: df$Name

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Explanation: A two-dimensional, tabular data structure in R.
Example: 

df <- data.frame(ID = c(1, 2, 3), Name = c("Alice", "Bob", "Charlie"))
df
  ID    Name
1  1   Alice
2  2     Bob
3  3 Charlie

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help(data.frame)
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Description
  The function data.frame() creates data frames, tightly coupled collections of variables 
     which share many of the properties of matrices and of lists, used as the fundamental 
     data structure by most of R's modeling software.

Usage
data.frame(..., row.names = NULL, check.rows = FALSE,
           check.names = TRUE, fix.empty.names = TRUE,
           stringsAsFactors = FALSE)

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pd.read_csv()
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import pandas as pf
df=pd.read_csv("../Resources/ibm.csv",index_col="Date",
   infer_datetime_format=True,parse_date=True)

import pandas as pd
from pathLib import Path
infile=Path("../Resources/ibm.csv")
df=pd.read_csv(infile,index_col="Date",infer_datetime_format=True,
parse_date=True)

def readCSV(infile):
    """
      Exaple:>>>infile=Path("../Resources/ibm.csv")
             >>>df=readCSV(infile)
    """
    df=pd.read_csv(infile,index_col="Date",infer_datetime_format=True,parse_date=True)
    return df
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Standard.Scaler
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from sklearn.processing import Standard.Scaler

a=Standard.Scaler()
b=a.fit(x_train)
x_train_scaled = b.transform(x_train)
x_test_scaled  = b.transform(x_test)

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