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Digital Modulation is the process of converting between bits and signals.Transmission MechanismsThe various modulation schemes result in various transmission mechanisms which are as follows −Baseband transmission.Passband transmission.Multiplexing TechniquesSharing of a transmission channel by various signals is called multiplexing. The different multiplexing techniques are as follows −Time division multiplexing.Frequency division multiplexing.Code division multiplexing.Now, let us discuss one of the digital modulation schemes.Baseband TransmissionBaseband transmission is transmission of the encoded signal using its own baseband frequencies i.e. without any shift to higher frequency ranges. It is used for short distances.Steps in Baseband TransmissionLet us understand the baseband transmission step by step.Step 1 ... Read More
Digital wireless communication is not a new idea. Earlier, Morse code implemented the wireless network. Now-a-days, the modern digital systems use wireless systems of the same idea as Morse code as implemented but with better performance.Categories of Wireless NetworksWireless Networks are divided into three categories as explained below −System InterconnectionIt is all about interconnecting the components of a computer using short-range radio. Some companies together design a short-range wireless network called Bluetooth to connect various components like monitor, keyboard, mouse, printer etc, without wires.In simplest form, system interconnection networks use the master-slave concept. The system unit is normally the master. ... Read More
Transmitting the data in the form of packets over the internet is called casting.Types of CastingsThe different types of casting are as follows −Unicast − Transmitting data from one host to another host (one-one)Broad cast − Transmitting data from one host to many host (one-all)Multicast − Transmitting data from one host to a particular group of host (one-many).Let us see each casting type in detail −UnicastTransmitting data from one source host to one destination host is called a unicast. It is called as a one to one transmission.For example − source Host IP Address 192.168.20.1 sending data to destination Host ... Read More
Computer network is a group of computers or nodes that are linked to each other to share information and resources. Whereas, IP addresses are generally represented by a 32-bit unsigned binary value. It is represented in a dotted decimal format.For example, 9.250.7.5 is a valid IP address.The IP address consists of a pair of numbers −IP address = Let see the pictorial representation of two hosts that are communicated with the help of Network and IP address.ExplanationStep 1 − The service that is used to convert the Domain name to IP address is called Domain Name Service.Step 2 − The ... Read More
IP addresses are generally represented by a 32-bit unsigned binary value. It is represented in a dotted decimal format. For example, 9.250.7.5 is a valid IP address.The IP address consists of a pair of numbers −IP address = Class-based IP addressesThe first bits of the IP address specify how the rest of the address should be separated into its network and host part. This IP address consists of network ID and Host ID.Classes of IP addressThere are 5 classes of IP address in computer network, which are as follows −Class AClass BClass CClass DClass EThe numbers of IP addresses possible ... Read More
The insert() method is used to add a column from another DataFrame. At first, let us create our first DataFrame −dataFrame1 = pd.DataFrame({"Car": ["Audi", "Lamborghini", "BMW", "Lexus"], "Place": ["US", "UK", "India", "Australia"], "Units": [200, 500, 800, 1000]})Now, let us create our second DataFrame −dataFrame2 = pd.DataFrame({"Model": [2018, 2019, 2020, 2021], "CC": [3000, 2800, 3500, 3300]})Car column added from DataFrame1 to DataFrame2# Car column to be added to the second dataframe fetched_col = dataFrame1["Car"]ExampleFollowing is the code −import pandas as pd dataFrame1 = pd.DataFrame({"Car": ["Audi", "Lamborghini", "BMW", "Lexus"], "Place": ["US", "UK", "India", "Australia"], "Units": [200, 500, ... Read More
Multiindex Data Frame is a data frame with more than one index. Let’s say the following is our csv stored on the Desktop −At first, import the pandas library and read the above CSV file −import pandas as pd df = pd.read_csv("C:/Users/amit_/Desktop/sales.csv") print(df)We will form the ‘Car‘ and ‘Place‘ columns of the Dataframe as the index −df = df.set_index(['Car', 'Place'])The DataFrame is now a multi-indexed DataFrame having the ‘Car‘ and ‘Place‘ columns as an index.Now, let us use groupby on the multiindex dataframe:res = df.groupby(level=['Car'])['UnitsSold'].mean() print(res)ExampleFollowing is the code −import pandas as pd df = pd.read_csv("C:/Users/amit_/Desktop/sales.csv") print(df) ... Read More
When it is required to find the most frequent character in a string, an empty dictionary is created, and the elements in the string are iterated over. When a character is found in the dictionary, it is increment, else it is assigned to 1. The maximum of the values in the dictionary is found, and assigned to a variable.ExampleBelow is a demonstration of the samemy_string = "Python-Interpreter" print ("The string is : ") print(my_string) max_frequency = {} for i in my_string: if i in max_frequency: max_frequency[i] += 1 else: max_frequency[i] ... Read More
When it is required to find the decreasing point in a list, a simple iteration and the ‘break’ statement are used.ExampleBelow is a demonstration of the same −my_list = [21, 62, 53, 94, 55, 66, 18, 1, 0] print("The list is :") print(my_list) my_result = -1 for index in range(0, len(my_list) - 1): if my_list[index + 1] < my_list[index]: my_result = index break print("The result is :") print(my_result)OutputThe list is : [21, 62, 53, 94, 55, 66, 18, 1, 0] The result is : 1ExplanationA list of integers is ... Read More
When it is required to get the count of the unique values in a list of tuple, ‘defaultdict’, ‘set’ operator and the ‘append’ method are used.ExampleBelow is a demonstration of the same −from collections import defaultdict my_list = [(12, 32), (12, 21), (21, 32), (89, 21), (71, 21), (89, 11), (99, 10), (8, 23), (10, 23)] print("The list is :") print(my_list) my_result = defaultdict(list) for element in my_list: my_result[element[1]].append(element[0]) my_result = dict(my_result) result_dictionary = dict() for key in my_result: result_dictionary[key] = len(list(set(my_result[key]))) print("The resultant list is :") print(result_dictionary)OutputThe list is ... Read More