Here you go with pandas 1 min concepts(which I share on insta reel)


https://github.com/Akansha-yadav24/Pandas-1-min-concepts.git



🫵More likes😍 more posts and resources 😇

cult.fit Hiring Fresher For Business Analyst
Location: Bangalore
Qualification: Bachelor/Master Degree
Work Experience: Freshers
Salary: 7 - 10 LPA

Apply Link: https://careers.cult.fit/#!/job-view/business-analyst-bangalore-business-analysis-2023081811283322

for Daily job Updates join here: https://t.me/Codingdidi ✅

❤️ Like for more ❤️

Hi, all

Another pandas long video DAY-7 is out on my yt channel.

Here are the link.


English:-

https://youtu.be/QXHKe30bFdY?si=pUwTz3LmvMcvcjmP



Hindi:- https://youtu.be/IN-B40L5m_A?si=oxWU8DWpM-0ngVxn

Go and check out the video.


🎯Don't forget to subscribe and hit the 🔔 bell icon ☺️.


Follow @codingdidi

FREE business analyst course by Microsoft and LINKEDIN

Link:-
https://www.linkedin.com/learning/paths/career-essentials-in-business-analysis-by-microsoft-and-linkedin



Follow @codingdidi

Hi 👋 All!

Learning Pandas day-8

English:-
https://youtu.be/8phiNzcCs7A?si=0hq1cGlpjtOi-tGJ


Hindi:-
https://youtu.be/HxfEWNidVd0?si=bMwyn9s95oHtva-g


Don't forget to like and comment on the 📷 video.


Subscribe to the channel.


I'm waiting for you all in the comment section 😉 ✅


Follow @codingdidi

Slice is hiring for a Data Analyst!
👇👇
https://www.linkedin.com/jobs/view/3915089117/

Google is hiring Data Scientist!
Qualification: Master’s degree or PhD
Salary: 11 - 29 LPA (Expected)
Batch: 2023/ 2024
Experience: Entry level
Location: Bangalore, India

📌Apply Now: https://www.google.com/about/careers/applications/jobs/results/82920494979785414-data-scientist-university-graduate-2024

Follow @codingdidi.

Complete Series to learn pandas!!

Utilities this weekend to learn pandas! 😉

Day-1 introduction to pandas,series and dataframe.
English:-
https://youtu.be/lrEk0RcpPzc?si=XjJyuarbBnhRh3kB
Hindi
https://youtu.be/mNGnGyIP9nw?si=_5SWLgchpS859VoB


Day-2 creates a series like a pro
English:-
https://youtu.be/lWNogRvSbtQ?si=_cha64qIhtMW3T4_
Hindi:-
https://youtu.be/xSrb_Cds-ws?si=VKgu5gEejQYRQKwO

Day-3 Create dataframe using 1-D
English:-
https://youtu.be/EbKzSqmS-Hg?si=UBc-sXJicpt5hD4D
Hindi:-
https://youtu.be/F3niR44_L38?si=XDhd06efdqG45IvU



Day-4 learn to save your files locally.
English:-
https://youtu.be/UaoseR5HnUY?si=hfhO60u-yEcaPddX
Hindi:-
https://youtu.be/jQTKaqRjVos?si=0mA09eyAjO986E2U

Day-5 Learn to load and view data(part-1)
English:-
https://youtu.be/CrvY0QIURyg?si=GaFgKfBb4VDbZzdP
Hindi
https://youtu.be/4NTWYUeuSWM?si=MjnASuNvMxjlmH1h

Day-6 methods to view your data(part-2)
English:-
https://youtu.be/DYSAc3Pmzwo?si=QzSS9k3SqLJ0r0hh
Hindi
https://youtu.be/r9H6ybaLWv4?si=q4Aazze7ihWKNnPF

Day-7 regex function and reset indexing
English:-
https://youtu.be/QXHKe30bFdY?si=K1PndEcX1bH0GYIC
Hindi:-
https://youtu.be/IN-B40L5m_A?si=dkQr-V_-Qw8-Qftq


Day-8 indexing vs Selection, how to do indexing.
English:- https://youtu.be/8phiNzcCs7A?si=CABGo9KUMw8wPYB5
Hindi
https://youtu.be/HxfEWNidVd0?si=SuYo6bu3-ZpnNpv0

More to come your way! 😄

GITHUB REPO LINK:- https://github.com/Akansha-yadav24/Learn-python-pandas-in-2024


Follow @codingdidi

Referral message template 👇

Follow @codingdidi

Hi [Name],

I hope this message finds you well. I am writing to ask if you would be willing to refer me for a job in your company. I recently came across a job opening that I believe suits my skills and experience, and I would be very grateful if you could provide a positive referral on my behalf.
I have attached my resume for your reference so you can get an idea of my qualifications. I would really appreciate any help you can provide.

Thank you for your time.

Sincerely,
[Your Name]

Looking for candidates for the role of AI/ML Developer (Computer Vision). If interested or you know someone who is a good fit. Please mail your resume at rohan.kaveri@conmove.io

Job Description: AI/ML Developer (Computer Vision)

Position: AI/ML Developer (Computer Vision)

Location: Viman Nagar,Pune

Job Type: Full-time

Responsibilities:

Collaborate with cross-functional teams to understand project requirements and objectives.
Develop and implement computer vision algorithms for object detection and recognition.
Train and fine-tune machine learning models using state-of-the-art techniques.
Evaluate model performance and iterate on improvements.
Utilize Python programming language and relevant libraries/frameworks (e.g., TensorFlow, PyTorch) for model development.

Requirements:

Bachelor's or Master's degree in Computer Science, Engineering, or related field.
Strong understanding of machine learning fundamentals and algorithms.
Proficiency in Python programming language.
Knowledge of computer vision concepts and techniques.
Experience with deep learning frameworks such as PyTorch.
Familiarity with object detection models (e.g., YOLO)
Ability to work collaboratively in a team environment.
Excellent problem-solving and analytical skills.
Experience with PowerBI or other BI tools is a plus, but not required.

FRND is hiring for a Business and Strategy Analyst!
👇👇
https://www.linkedin.com/jobs/view/3913130927

Coming live in 20 min for your queries.!

Link is here
https://youtube.com/@codingdidi-hindi?si=5w6wfM2i_mel2cfp

Let's chat at 9:00pm

Microsoft is hiring Data Analyst
👇👇
https://jobs.careers.microsoft.com/us/en/job/1716412/Data-Analyst?jobsource=linkedin

50 𝐨𝐟 𝐭𝐡𝐞 𝐦𝐨𝐬𝐭 𝐢𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐄𝐱𝐜𝐞𝐥 𝐟𝐨𝐫𝐦𝐮𝐥𝐚𝐬 𝐭𝐡𝐚𝐭 𝐜𝐚𝐧 𝐡𝐞𝐥𝐩 𝐲𝐨𝐮 𝐩𝐞𝐫𝐟𝐨𝐫𝐦 𝐯𝐚𝐫𝐢𝐨𝐮𝐬 𝐭𝐚𝐬𝐤𝐬 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐭𝐥𝐲.


S𝐔𝐌: Adds up numbers in a range.
𝐀𝐕𝐄𝐑𝐀𝐆𝐄: Calculates the average of numbers in a range.
𝐌𝐀𝐗: Returns the largest number in a range.
𝐌𝐈𝐍: Returns the smallest number in a range.
𝐂𝐎𝐔𝐍𝐓: Counts the number of cells that contain numbers in a range.
𝐂𝐎𝐔𝐍𝐓𝐀: Counts the number of non-empty cells in a range.
𝐈𝐅: Checks if a condition is met and returns one value if true and another value if false.
𝐕𝐋𝐎𝐎𝐊𝐔𝐏: Searches for a value in the first column of a table and returns a value in the same row from another column.
𝐇𝐋𝐎𝐎𝐊𝐔𝐏: Similar to VLOOKUP, but searches for a value in the first row of a table.
𝐈𝐍𝐃𝐄𝐗: Returns the value of a cell in a specific row and column of a range.
𝐌𝐀𝐓𝐂𝐇: Returns the relative position of an item in a range.
𝐂𝐎𝐍𝐂𝐀𝐓𝐄𝐍𝐀𝐓𝐄: Joins two or more text strings into one string.
𝐋𝐄𝐅𝐓: Returns the leftmost characters from a text string.
𝐑𝐈𝐆𝐇𝐓: Returns the rightmost characters from a text string.
𝐋𝐄𝐍: Returns the number of characters in a text string.
𝐓𝐑𝐈𝐌: Removes leading and trailing spaces from a text string.
𝐔𝐏𝐏𝐄𝐑: Converts text to uppercase.
𝐋𝐎𝐖𝐄𝐑: Converts text to lowercase.
𝐏𝐑𝐎𝐏𝐄𝐑: Capitalizes the first letter of each word in a text string.
𝐓𝐄𝐗𝐓: Formats a number or date value as text using a specified format.
𝐃𝐀𝐓𝐄: Returns the serial number of a particular date.
𝐓𝐎𝐃𝐀𝐘: Returns the current date.
𝐍𝐎𝐖: Returns the current date and time.
𝐃𝐀𝐓𝐄𝐃𝐈𝐅: Calculates the difference between two dates in years, months, or days.
𝐄𝐎𝐌𝐎𝐍𝐓𝐇: Returns the last day of the month, n months before or after a given date.
𝐑𝐎𝐔𝐍𝐃: Rounds a number to a specified number of digits.
𝐑𝐎𝐔𝐍𝐃𝐔𝐏: Rounds a number up, away from zero, to the nearest multiple of significance.
𝐑𝐎𝐔𝐍𝐃𝐃𝐎𝐖𝐍: Rounds a number down, toward zero, to the nearest multiple of significance.
𝐈𝐅𝐄𝐑𝐑𝐎𝐑: Returns a value you specify if a formula evaluates to an error, otherwise returns the result of the formula.
𝐒𝐔𝐌𝐈𝐅: Adds the cells specified by a given condition or criteria.
𝐒𝐔𝐌𝐈𝐅𝐒: Adds the cells in a range that meet multiple criteria.
𝐀𝐕𝐄𝐑𝐀𝐆𝐄𝐈𝐅: Calculates the average of cells specified by a given condition or criteria.
𝐀𝐕𝐄𝐑𝐀𝐆𝐄𝐈𝐅𝐒: Calculates the average of cells that meet multiple criteria.
𝐂𝐎𝐔𝐍𝐓𝐈𝐅: Counts the number of cells specified by a given condition or criteria.
COUNTIFS: Counts the number of cells that meet multiple criteria.
RAND: Returns a random number between 0 and 1.
RANDBETWEEN: Returns a random number between the numbers you specify.
PI: Returns the value of pi (3.14159265358979).
POWER: Raises a number to a power.
SQRT: Returns the square root of a number.
LOG: Returns the logarithm of a number to the base you specify.
EXP: Returns e raised to the power of a given number.
MOD: Returns the remainder of a division operation.
INT: Rounds a number down to the nearest integer.
ABS: Returns the absolute value of a number.
AND: Returns TRUE if all its arguments are TRUE, and FALSE otherwise.
OR: Returns TRUE if any argument is TRUE, and FALSE otherwise.
NOT: Returns the opposite of a logical value.
SUMPRODUCT: Multiplies corresponding components in the given arrays, and returns the sum of those products.
TRANSPOSE: Transposes rows and columns in a range of cells.


❤️More likes more posts..! 🫶


Follow @codingdidi

⚠️Hiring ⚠️

Rocket Learning is #hiring for Data Analytics Intern (paid).

Skills: SQL, Excel, etc.

Send your resume at
eklavya.s@rocketlearning.org

Pandas and Numpy Interview Questions for Data/ Business Analysts

Question 1: You have a NumPy array representing student grades. How would you filter the array to extract only the grades above a certain threshold?

Question 2: Explain the difference between 'drop_duplicates()' and 'duplicated()' methods in Pandas. Provide a code example demonstrating their usage.

Question 3: Describe the usage of 'at' and 'iat[]' in Pandas for accessing DataFrame elements. How do they differ from 'loc[]' and 'iloc[]'?

Question 4: You have a DataFrame containing sales data with columns 'ProductID', 'Category', and 'Sales'. How would you use the 'groupby()' method to calculate total sales for each category?

Question 5: Discuss the benefits of using list comprehensions over traditional for loops in Python. Can you provide an example where list comprehensions improve code readability and efficiency?

Question 6: What is the purpose of the 'apply()' function in Pandas? Can you provide a scenario where it's advantageous over other methods?

Question 7: You are provided with a Pandas DataFrame that contains a column with date strings. How would you convert this column to a datetime format? Additionally, how would you extract the month and year from these datetime objects?

Question 8: Describe how to perform array indexing and slicing in NumPy. Provide examples demonstrating different indexing and slicing techniques.

Question 9: You have a DataFrame containing columns 'Name', 'Age', and 'Gender'. How would you filter the DataFrame to extract only the rows where Age is greater than 30 and Gender is 'Female'?

Question 10: Describe the benefits of using the 'pd.merge()' function over other methods like 'DataFrame.join()' for merging DataFrames in Pandas. Can you provide a scenario where 'pd.merge()' is advantageous?


Follow @codingdidi

Seagate Technology Hiring Fresher For Intern - Data Science

Follow @codingdidi

Location: Pune, IN
Qualification: Bachelor/Master Degree
Work Experience: Freshers

https://www.linkedin.com/feed/update/urn:li:share:7193249948732125184/

Another pandas video is live, do check it out !! 📸

English:-
https://youtu.be/i7fxyW9613E?si=vkbkyT2lRmHpyxBB


Hindi:- https://youtu.be/o0k8htG3wss?si=NqJ7XpxFTgIbXwM_


Don't forget to comment.
I'm waiting for you all in comments! 🙏.

✅Follow Codingdidi ✅

💼 JP Morgan is Hiring for 2024
 
📊 Role:- Data Scientist

🏙️ Job Location:- Bangalore

🎓 Qualification:- Graduation

💰 Salary:- Upto ₹ 10 LPA

🔗 Link- https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/job/210512985?utm_medium=symphonytalent-jobads&utm_campaign=Default%20Campaign&utm_content=Data%20Scientist-%20Analyst&utm_term=210512985&utm_source=Indeed