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SQL Interview Success: Unlocking the Top 5 Frequently Asked Queries

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 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 Interviews 01. Joins The 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 ---- 1 1 2 3 Table2 -------- id ---- 1 3 1 NULL Output ------- Inner join --------------- 5 rows will return The result will be: =============== 1  1 1   1 1   1 1    1 3    3 02. Substring and Concat Here, we need to write an SQL query to make the upper case of the first letter and the small case of the remaining letter. Table1 ------ ename ===== raJu venKat kRIshna Solution: ========== SELECT CONCAT(UPPER(SUBSTRING(name, 1, 1)), LOWER(SUBSTRING(name, 2))) AS capitalized_name FROM Table1; 03. Case statement SQL Query ========= SELECT Code1, Code2,      CASE         WHEN Code1 = 'A' AND Code2 = 'AA' THEN "A" | "A
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How to Read CSV file Data in Python

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Here is a way to read CSV files in Python pandas. The packages you need to import are numpy and pandas. On the flip side, for Text files, you don't need to import these special libraries since python by default support it.



pandas read_csv


Python pandas read_csv


>>> import numpy as np
>>> import pandas as pd


To see how pandas handle this kind of data, we'll create a small CSV file in the working directory as ch05_01.csv.

white, red, blue, green, animal
1,5,2,3,cat 
2,7,8,5,dog 
3,3,6,7,horse 
2,2,8,3,duck 
4,4,2,1,mouse


Since this file is comma-delimited, you can use the read_csv() function to read its content and convert it to a dataframe object.
>>> csvframe = pd.read_csv('ch05_01.csv')
>>> csvframe
   white  red  blue  green animal
0      1    5     2      3    cat
1      2    7     8      5    dog
2      3    3     6      7  horse
3      2    2     8      3   duck
4      4    4     2      1  mouse


Python reading text files


Since python supports text files, you don't need to import NumPy and Pandas. The syntax is a little different. 

Using the Open method, here file is opened with read mode. In the place file name, it has given; the full path of the file. The Print method displays contents. Here read method is used to read the file.

# Open our file in read mode 
f = open("data/flatland01.txt", mode="r") 
# Read and display the text file 
print(f.read())
# Close our file resource 
f.close()

Finally, working with CSV and Text files knowing is helpful for interviews.


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