pygaurav

import pandas as pd

list_of_names = ["Ron","Jeremy","Rohit","Brian","Rich"]
roll_number = [1,2,3,4,5]

series = pd.Series(data=list_of_names,index=roll_number)
series

pygaurav

import pandas as pd

dict_of_information = {
        1:"Ron",
        2:"Jeremy",
        3:"Rohit",
        4:"Brian",
        500:"Rich"
        }

pygaurav

import pandas as pd

list_of_names = ["Ron","Jeremy","Rohit","Brian","Rich"]

series = pd.Series(data=list_of_names)
series

pygaurav

import pandas as pd

list_of_names_1 = ["Ron","Jeremy","Rohit","Brian","Rich"]
list_of_names_l = ["Harris","Brack","Shetty","Van","Cherodio"]

series1 = pd.Series(data=list_of_names)
series2 = pd.Series(data=list_of_names)
finalseries = series1+" "+series2
finalseries

pygaurav

import pandas as pd

list_of_numbers1 = [100,200,300,400,500]
index_number1 = [1,2,3,4,5]

list_of_numbers2 = [200,300,400,500,600]
index_number2 = [10,20,30,40,50]

series1 = pd.Series(data=list_of_numbers1,index=index_number1)
series2 = pd.Series(data=list_of_numbers2,index=index_number2)

pygaurav

import pandas as pd

list_of_numbers1 = [100,200,300,400,500]
index_number1 = [1,2,3,4,5]

list_of_numbers2 = [200,300,400,500,600]
index_number2 = [10,20,30,40,50]

series1 = pd.Series(data=list_of_numbers1,index=index_number1)
series2 = pd.Series(data=list_of_numbers2,index=index_number2)

pygaurav

import pandas as pd

column_names = ["sepal length","sepal width","petal length","petal width","Type of flower"]
df = pd.read_csv("https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data",
                 names=column_names)
df.head()

pygaurav

import pandas as pd

column_names = ["sepal length","sepal width","petal length","petal width","Type of flower"]
df = pd.read_csv("https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data",
                 names=column_names)
df.describe()

pygaurav

import pandas as pd

column_names = ["sepal length","sepal width","petal length","petal width","Type of flower"]
df = pd.read_csv("https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data",
                 names=column_names)
df.shape

pygaurav

import pandas as pd

column_names = ["sepal length","sepal width","petal length","petal width","Type of flower"]
df = pd.read_csv("https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data",
                 names=column_names)
print("The shape of dataframe is {0}".format(df.shape))
print("The dimension of dataframe is {0}".format(df.ndim))
print("The size of dataframe is {0}".format(df.size))
print("The dtype of data is {0}".format(df.dtypes))
print("The values of data is {0}".format(df.values))