tag:blogger.com,1999:blog-12108499471513273432024-03-18T08:33:50.554+05:30 ApplyBigAnalytics Data Engineer's MentorSrinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.comBlogger614125tag:blogger.com,1999:blog-1210849947151327343.post-18914072310473223022024-03-10T17:07:00.003+05:302024-03-10T17:07:59.861+05:30SQL Interview Success: Unlocking the Top 5 Frequently Asked Queries Here are the five top commonly asked SQL queries in the interviews. These you can expect in Data Analyst, or, Data Engineer interviews.Top SQL Queries for Interviews01. JoinsThe commonly asked question pertains to providing two tables, determining the number of rows that will return on various join types, and the resultant.Table1--------id----1123Table2--------id----131NULLOutput------Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-27394752845559769982024-02-11T18:44:00.001+05:302024-02-11T18:44:12.728+05:30SQL Query: 3 Methods for Calculating Cumulative SUM SQL provides various constructs for calculating cumulative sums, offering flexibility and efficiency in data analysis. In this article, we explore three distinct SQL queries that facilitate the computation of cumulative sums. Each query leverages different SQL constructs to achieve the desired outcome, catering to diverse analytical needs and preferences.Using Window Functions (e.g., PostgreSQL,Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-63250458457400889272024-01-07T17:59:00.000+05:302024-01-07T17:59:09.002+05:30AWS CLI PySpark a Beginner's Comprehensive GuideAWS (Amazon Web Services) and PySpark are separate technologies, but they can be used together for certain purposes. Let me provide you with a beginner's guide for both AWS and PySpark separately.AWS (Amazon Web Services):Amazon Web Services (AWS) is a cloud computing platform that offers a wide range of services for computing power, storage, databases, machine learning, analytics, and more.1. Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-46812024690763243692023-12-15T12:56:00.005+05:302024-01-03T12:18:59.288+05:3015 Top Data Analyst Interview Questions: Read Now We will explore the world of data analysis using Python, covering topics such as data manipulation, visualization, machine learning, and more. Whether you are a beginner or an experienced data professional, join us on this journey as we dive into the exciting realm of Python analytics and unlock the power of data-driven insights. Let's harness Python's versatility and explore the endless Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-36437787372552439382023-11-25T11:50:00.003+05:302024-01-03T16:15:22.098+05:30How to Deal With Missing Data: Pandas Fillna() and Dropna()Here are the best examples of Pandas fillna(), dropna() and sum() methods. We have explained the process in two steps - Counting and Replacing the Null values.Count Nulls## count null values column-wisenull_counts = df.isnull().sum()print(null_counts)```Output:```Column1 1Column2 1Column3 5dtype: int64```In the above code, we first create a sample Pandas Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-29846018798994563442023-11-11T18:41:00.002+05:302023-11-11T18:41:28.163+05:30How to Effectively Parse and Read Different Files in PythonHere is Python logic that shows Parse and Read Different Files in Python. The formats are XML, JSON, CSV, Excel, Text, PDF, Zip files, Images, SQLlite, and Yaml.Python Reading Filesimport pandas as pdimport jsonimport xml.etree.ElementTree as ETfrom PIL import Imageimport pytesseractimport PyPDF2from zipfile import ZipFileimport sqlite3import yamlReading Text Files# Read text file (.txt)def Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-39527262939277156762023-10-20T10:59:00.001+05:302023-10-20T10:59:10.231+05:30A Beginner's Guide to Pandas Project for Immediate PracticePandas is a powerful data manipulation and analysis library in Python that provides a wide range of functions and tools to work with structured data. Whether you are a data scientist, analyst, or just a curious learner, Pandas can help you efficiently handle and analyze data. In this blog post, we will walk through a step-by-step guide on how to start a Pandas project from scratch. By Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-29051270656229926102023-10-08T21:00:00.001+05:302023-10-08T21:00:11.873+05:30How to Write Complex Python Script: Explained Each Step Creating a complex Python script is challenging, but I can provide you with a simplified example of a script that simulates a basic bank account system. In a real-world application, this would be much more elaborate, but here's a concise version.Python Complex ScriptHere is an example of a Python script that explains each step:class BankAccount: def __init__(self, Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-33095837693050687222023-09-23T19:06:00.001+05:302023-09-23T19:06:35.191+05:30Python Regex: The 5 Exclusive Examples Regular expressions (regex) are powerful tools for pattern matching and text manipulation in Python. Here are five Python regex examples with explanations:01 Matching a Simple Patternimport retext = "Hello, World!"pattern = r"Hello"result = re.search(pattern, text)if result: print("Pattern found:", result.group())Output:Output:Pattern found: HelloThis example searches for the Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-78020068240598163792023-08-27T16:51:00.001+05:302023-08-27T16:51:44.607+05:30Best Practices for Handling Duplicate Elements in Python ListsHere are three awesome ways that you can use to remove duplicates in a list. These are helpful in resolving your data analytics solutions. 01. Using a SetConvert the list into a set, which automatically removes duplicates due to its unique element nature, and then convert the set back to a list.Solution:original_list = [2, 4, 6, 2, 8, 6, 10]unique_list = list(set(original_list))02. Using a Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-10522154404458339712023-08-18T15:12:00.003+05:302023-08-18T15:29:49.117+05:3010 Exclusive Python Projects for InterviewsHere are ten Python projects along with code and possible solutions for your practice.01. Palindrome Checker:Description: Write a function that checks if a given string is a palindrome (reads the same backward as forward).def is_palindrome(s): s = s.lower().replace(" ", "") return s == s[::-1]# Test the functionprint(is_palindrome("radar")) # Output: Trueprint(Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-43563671361305570972023-08-10T13:30:00.002+05:302023-08-10T13:30:10.706+05:30How to Fill Nulls in Pandas: bfill and ffillIn Pandas, bfill and ffill are two important methods used for filling missing values in a DataFrame or Series by propagating the previous (forward fill) or next (backward fill) valid values respectively. These methods are particularly useful when dealing with time series data or other ordered data where missing values need to be filled based on the available adjacent values.ffill (forward fill):Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-80897214045022995862023-07-30T18:06:00.008+05:302023-07-30T18:23:33.812+05:30How to Handle Spaces in PySpark Dataframe ColumnIn PySpark, you can employ SQL queries by importing your CSV file data to a DataFrame. However, you might face problems when dealing with spaces in column names of the DataFrame. Fortunately, there is a solution available to resolve this issue.Reading CSV file to DataframeHere is the PySpark code for reading CSV files and writing to a DataFrame.#initiate sessionspark = SparkSession.builder \ .Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-50435399236748754872023-07-20T19:41:00.004+05:302023-07-20T19:42:15.995+05:30How to Convert Dictionary to Dataframe: Pandas from_dict Pandas is a data analysis Python library. The example shows you to convert a dictionary to a data frame. The point to note here is DataFrame will take only 2D data. So you need to supply 2D data. Pandas Dictionary to Dataframeimport pandas as pdimport numpy as npdata_dict = {'item1' : np.random.randn(4), 'item2' : np.random.randn(4)}df3=pd.DataFrame.from_dict(data_dict, orient='Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-42915476904922359142023-07-07T18:38:00.011+05:302023-07-13T17:13:48.230+05:30The Easy Way to Split String Python Partition MethodHere's a way without the Split function you can split (or extract) a substring. In Python the method is Partition. You'll find here how to use this method with an example. How to Split the string using Partition method Returns Left side partExample-1my_string='ABCDEFGH||10||123456.25|'my_partition=my_string.partition('|')[0]print(my_partition)Output|10||123456.25|** Process exited - Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-76317042976432539662023-06-24T18:02:00.007+05:302023-07-13T21:31:11.484+05:305 Python Pandas Tricky Examples for Data AnalysisHere are five tricky Python Pandas examples. These provide detailed insights to work with Pandas in Python,#1 Dealing with datetime data (parse_dates pandas example)import pandas as pd# Convert a column to datetime formatdata['date_column'] = pd.to_datetime(data['date_column'])# Extract components from datetime (e.g., year, month, day)data['year'] = data['date_column'].dt.yeardata['month'] = dataSrinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-66039149125354700542023-06-10T19:53:00.001+05:302023-06-27T22:13:05.949+05:302 User Input Python Sample ProgramsHere are the Python programs that work on taking user input and giving responses to the user. These are also called interactive programs. Python enables you to read user input from the command line via the input() function or the raw_input() function. Typically, you assign user input to a variable containing all characters that users enter from the keyboard. User input terminates when users Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-41633494668287037012023-05-28T17:30:00.000+05:302023-05-28T17:30:06.282+05:30The Quick and Easy Way to Analyze Numpy Arrays The quickest and easiest way to analyze NumPy arrays is by using the numpy.array() method. This method allows you to quickly and easily analyze the values contained in a numpy array. This method can also be used to find the sum, mean, standard deviation, max, min, and other useful analysis of the value contained within a numpy array.SumYou can find the sum of Numpy arrays using the np.sum() Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-67336439614229276552023-05-16T16:45:00.006+05:302023-05-18T18:14:18.681+05:30These 10 Skills You Need to Become Data Analyst To become a data analyst with Python, there are several technical skills you need to learn. Here are the key ones:#1 Python ProgrammingPython is widely used in data analysis due to its simplicity, versatility, and the availability of powerful libraries. You should have a strong understanding of Python fundamentals, including data types, variables, loops, conditional statements, functions, and Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-81403402666406552252023-05-07T17:37:00.003+05:302023-05-07T17:37:36.356+05:30How to Find Non-word Character: Python Regex ExampleIn Python, the regular expression pattern \W matches any non-word character. Here's an example of usage. The valid word characters are [a-zA-Z0-9_]. \W (upper case W) matches any non-word character.Regex examples to find non-word char#1 Exampleimport retext = "Hello, world! How are you today?"non_words = re.findall(r'\W', text)print(non_words)In the above example, the re.findall() function is Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-54055656474383779002023-04-27T10:49:00.002+05:302023-04-30T08:50:55.732+05:30How to Write ETL Logic in Python: Sample Code to PracticeHere's an example Python code that uses the mysql-connector library to connect to a MySQL database, extract data from a table, transform it, and load it as a JSON file. Here's an example:Python ETL Sample Codeimport mysql.connectorimport json# Connect to the MySQL databasecnx = mysql.connector.connect(user='username', password='password', &Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-74627996336388971482023-04-16T19:01:00.005+05:302023-05-03T14:36:29.112+05:30Quick Guide to AI Prompt EngineeringHere are roles & responsibilities of AI prompt engineer, which has growing demand in the USA and the rest of the world. The new Prompt engineering is a process that designs effective and engaging conversation starters for chatbots and virtual assistants. Guide on Prompt EngineeringA key aspect of chatbot development, prompt engineering involves a deep understanding of user interests and Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-69491944485398203702023-04-11T13:32:00.003+05:302023-04-27T17:40:29.193+05:30 How to Write Lambda Function Quickly in Python: 5 ExamplesHere are the top python lambda function examples for your project and interviews. "Python's lambda functions are a powerful way to create small, anonymous functions on the fly. In this post, we'll explore some examples of how to use lambda functions in Python.5 Best Python Lambda Function Examples#1 Sorting a List of Tuples by the Second ElementThis lambda function sorts a list of tuples based onSrinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-54732657724239003992023-04-02T11:22:00.001+05:302023-04-19T19:49:00.996+05:30 The Quick and Easy Way to Fix Python UnboundLocalErrorHere is the easy way to fix the issue of the Python UnboundLocalError, allowing users to resolve any problems quickly.Python UnboundLocalErrorWhile the variable in the function has already been defined, during execution, the result prints with an error of UnboundLocalError. Below, you will find an example that explains the issue and resolution.Error: file 'example.txt' not foundTraceback (most Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0tag:blogger.com,1999:blog-1210849947151327343.post-73905742420413606142023-03-22T21:32:00.008+05:302023-03-31T15:47:33.226+05:30Scraping Website: How to Write a Script in PythonHere's a python model script to scrape a website using the BeautifulSoup.Python scriptThe logic below uses BeautifulSoup Package for web scraping.import requestsfrom bs4 import BeautifulSoupurl = "https://www.example.com"response = requests.get(url)soup = BeautifulSoup(response.text, "html.parser")# Print the title of the webpageprint(soup.title.text)# Print all the links in the webpagefor link Srinihttp://www.blogger.com/profile/07397528550702315947noreply@blogger.com0