Data Analyst Interview Resources
Join our telegram channel to learn how data analysis can reveal fascinating patterns, trends, and stories hidden within the numbers! 📊 For ads & suggestions: @love_data
إظهار المزيد📈 نظرة تحليلية على قناة تيليجرام Data Analyst Interview Resources
تُعد قناة Data Analyst Interview Resources (@dataanalystinterview) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 52 304 مشتركاً، محتلاً المرتبة 3 375 في فئة التعليم والمرتبة 6 715 في منطقة الهند.
📊 مؤشرات الجمهور والحراك
منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 52 304 مشتركاً.
بحسب آخر البيانات بتاريخ 28 أكتوبر, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار -247، وفي آخر 24 ساعة بمقدار -12، مع بقاء الوصول العام مرتفعاً.
- حالة التحقق: غير موثّقة
- معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 2.31%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 0.75% من ردود الفعل نسبةً إلى إجمالي المشتركين.
- وصول المنشورات: يحصل كل منشور على متوسط 1 206 مشاهدة. وخلال اليوم الأول يجمع عادةً 394 مشاهدة.
- التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 4.
- الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل sql, row, |--, dataset, visualization.
📝 الوصف وسياسة المحتوى
يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
“Join our telegram channel to learn how data analysis can reveal fascinating patterns, trends, and stories hidden within the numbers! 📊
For ads & suggestions: @love_data”
بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 29 أكتوبر, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التعليم.
.dropna(), .fillna() functions to do this easily.
4. What are list comprehensions and how are they useful?
Concise syntax to create lists from iterables using a single readable line, often replacing loops for cleaner and faster code.
Example: [x**2 for x in range(5)] → ``
5. Explain Pandas DataFrame and Series.
⦁ Series: 1D labeled array, like a column.
⦁ DataFrame: 2D labeled data structure with rows and columns, like a spreadsheet.
6. How do you read data from different file formats (CSV, Excel, JSON) in Python?
Using Pandas:
⦁ CSV: pd.read_csv('file.csv')
⦁ Excel: pd.read_excel('file.xlsx')
⦁ JSON: pd.read_json('file.json')
7. What is the difference between Python’s append() and extend() methods?
⦁ append() adds its argument as a single element to the end of a list.
⦁ extend() iterates over its argument adding each element to the list.
8. How do you filter rows in a Pandas DataFrame?
Using boolean indexing:
df[df['column'] > value] filters rows where ‘column’ is greater than value.
9. Explain the use of groupby() in Pandas with an example.
groupby() splits data into groups based on column(s), then you can apply aggregation.
Example: df.groupby('category')['sales'].sum() gives total sales per category.
10. What are lambda functions and how are they used?
Anonymous, inline functions defined with lambda keyword. Used for quick, throwaway functions without formally defining with def.
Example: df['new'] = df['col'].apply(lambda x: x*2)
React ♥️ for Part 2[]
⦁ Tuple: immutable, defined with ()
lst = [1, 2, 3]
tpl = (1, 2, 3)
2️⃣ How to reverse a string in Python?
s = "Hello"
rev = s[::-1] # 'olleH'
3️⃣ Write a function to find factorial using recursion.
def factorial(n):
return 1 if n == 0 else n * factorial(n-1)
4️⃣ How do you handle exceptions?
⦁ Use try and except blocks.
try:
x = 1 / 0
except ZeroDivisionError:
print("Cannot divide by zero")
5️⃣ Difference between == and is?
⦁ == compares values
⦁ is compares identities (memory locations)
6️⃣ How to check if a number is prime?
def is_prime(n):
if n < 2:
return False
for i in range(2,int(n**0.5)+1):
if n % i == 0:
return False
return True
7️⃣ What are list comprehensions? Give example.
⦁ Compact way to create lists
squares = [x*x for x in range(5)]
8️⃣ How to merge two dictionaries?
⦁ Python 3.9+
d1 = {'a':1}
d2 = {'b':2}
merged = d1 | d2
9️⃣ Explain *args and **kwargs.
⦁ *args: variable number of positional arguments
⦁ **kwargs: variable number of keyword arguments
10️⃣ How do you read a file in Python?
with open('file.txt', 'r') as f:
data = f.read()
Python Interview Resources: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L
Tap ❤️ for moreSELECT department, AVG(salary)
FROM employees
WHERE salary > 3000
GROUP BY department
HAVING AVG(salary) > 5000;
2. Write a query to find the second-highest salary.
Solution:
SELECT MAX(salary) AS second_highest_salary
FROM employees
WHERE salary < (SELECT MAX(salary) FROM employees);
3. How do you fetch the first 5 rows of a table?
Solution:
SELECT * FROM employees
LIMIT 5; -- (MySQL/PostgreSQL)
For SQL Server:
SELECT TOP 5 * FROM employees;
4. Write a query to find duplicate records in a table.
Solution:
SELECT column1, column2, COUNT(*)
FROM table_name
GROUP BY column1, column2
HAVING COUNT(*) > 1;
5. How do you find employees who don’t belong to any department?
Solution:
SELECT *
FROM employees
WHERE department_id IS NULL;
6. What is a JOIN, and write a query to fetch data using INNER JOIN.
Solution:
A JOIN combines rows from two or more tables based on a related column.
SELECT e.name, d.department_name
FROM employees e
INNER JOIN departments d ON e.department_id = d.id;
7. Write a query to find the total number of employees in each department.
Solution:
SELECT department_id, COUNT(*) AS total_employees
FROM employees
GROUP BY department_id;
8. How do you fetch the current date in SQL?
Solution:
SELECT CURRENT_DATE; -- MySQL/PostgreSQL
SELECT GETDATE(); -- SQL Server
9. Write a query to delete duplicate rows but keep one.
Solution:
WITH CTE AS (
SELECT *, ROW_NUMBER() OVER (PARTITION BY column1, column2 ORDER BY id) AS rn
FROM table_name
)
DELETE FROM CTE WHERE rn > 1;
10. What is a Common Table Expression (CTE), and how do you use it?
Solution:
A CTE is a temporary result set defined within a query.
WITH EmployeeCTE AS (
SELECT department_id, COUNT(*) AS total_employees
FROM employees
GROUP BY department_id
)
SELECT * FROM EmployeeCTE WHERE total_employees > 10;
Hope it helps :)
#sql #dataanalysts