This repository is a collection of the data interview questions from the mailing list run by InterviewQs. Slowly I will try and provide my answers for each of them - mostly as a self improvement exercise.

Note: the InterviewQs people currently charge $9 a month for the answers - which I don't subscribe to - therefore, the any answers in this repository are mine only and may or may not even be correct.

Note: The mailings do not always seem to make it to me, so where I don't have the data for the problem I will leave a marker, the intention being to fill the details in later if I manage to get hold of it.

answers to few questions https://github.com/nabaskes/InterviewQs

• Question 1 - Fradulent retail accounts
• Question 2 - Calculating a moving average using python
• Question 3 - The carshare dilemma
• Question 4 - Active users on a messaging application
• Question 5 - Employee survey results
• Question 6 - Python function to express power sets
• Question 7 - Probability of passing through interview stages
• Question 8 - Python function to traverse a binary tree path
• Question 9 - Time for a response on a messaging application
• Question 10 - Calculating student attendance using SQL
• Question 11 - Bias-Variance Tradeoff
• Question 12 - Finding the value closest to 0
• Question 13 - Cleaning and analyzing employee data
• Question 14 - Popular songs
• Question 15 - Drawing cards from a standard deck
• Question 16 - Points within an interval
• Question 17 - Analyzing employee data using Python
• Question 18 - A hotel chain's loyal customers
• Question 19 - New strain of flu
• Question 20 - One edit away
• Question 21 - Expanding a data set
• Question 22 - Picking a survey group
• Question 23 - Drawing cards from a standard deck, once more
• Question 24 - Oh foo-ie!
• Question 25 - Application feedback
• Question 26 - Is red independent from an ace?
• Question 27 - Property revenue across cities)
• Question 28 - Winning the lottery)
• Question 29 - American Football Scoring)
• Question 30 - Assigning grades)
• Question 31 - Life expectancy)
• Question 32 - Revenue per employee)
• Question 33 - Testing a claim around student intelligence)
• Question 34 - Identifying prime numbers with Python)
• Question 35 - Filtering student information with Pandas)
• Question 36 - Rolling to win!)
• Question 37 - Employees who are managers)
• Question 38 - Calculating earnings with Python)
• Question 39 - Normalizing student grades with Pandas)
• Question 40 - Calculating monthly revenue growth in SQL)
• Question 41 - Rolling dice to win...again)
• Question 42 - Sentiment analysis for app reviews
• Question 43 - Revenue trends for online vs. in store channels
• Question 44 - Joining to get total sales, a SQL problem
• Question 45 - Defective gaskets
• Question 46 - Smallest missing number in array
• Question 47 - Bayes' Theorem
• Question 48 - Top selling products
• Question 49 - Skittles from a bag
• Question 50 - Python function to count tuple elements
• Question 51 - Counting capital letters
• Question 52 - Naive Bayes
• Question 53 - Planning for a new office location, using SQL
• Question 54 - Sell, sell, sell!
• Question 55 - Categorizing foods
• Question 56 - Twitch content creators
• Question 57 - Probability of selecting a wardrobe
• Question 58 - Longest palindrome substring
• Question 59 - Chipotle item analysis
• Question 60 - Choosing two ice creams
• Question 61 - Ranking vendors by spend
• Question 62 - Subarray sums
• Question 63 - Baby names
• Question 64 - Reddit posts and comments
• Question 65 - Rolling 10 times
• Question 66 - Matrix frequencies
• Question 67 - Drop rows in dataframe that are between two dates
• Question 68 - Type I vs Type II error
• Question 69 - Airbnb stays by country
• Question 70 - Stepping through nested while loops in Python
• Question 71 - Employee tenure
• Question 72 - Shoe prices
• Question 73 - Testing the toxicity of water
• Question 74 - Temperature Conversion
• Question 75 - Retail revenue trends
• Question 76 - Resampling
• Question 77 - State populations
• Question 78 - Largest elements in an array
• Question 79 - Channel attribution
• Question 80 - Days to first sale
• Question 81 - Relationship between fitness and smoking
• Question 82 - Count of Triplet
• Question 83 - Sales by marketing channel using Pandas
• Question 84 - In SQL, 0 = 0?
• Question 85 - Testing user conversion
• Question 86 - Alternative array sorting
• Question 87 - Best ad group
• Question 88 - Best ad group, a SQL version
• Question 89 - Confidence intervals for a dataset
• Question 90 - Spiral matrix
• Question 91 - Replacing bad data with Pandas
• Question 92 - SQL Patterns
• Question 93 - Rental Car Locations
• Question 94 - Reverse it
• Question 95 - User messaging
• Question 96 - Tallying up absent students using SQL
• Question 97 - Life expectancy, revisited
• Question 98 - Counting numbers, letters, and other things from a text file
• Question 99 - Plotting stock prices
• Question 100 - Reddit comment activity
• Question 101 - Pricing a Coin Toss
• Question 102 - Births by state
• Question 103 - Cleaning termination dates
• Question 104 - Termination survey data
• Question 105 - Car Battery
• Question 106 - Histogram of years worked
• Question 107 - Customer recency (a multi-question problem)
• Question 108 - Twitch view times by creators
• Question 109 - Weather forecasting, a Markov Chain problem
• Question 110 - Customer frequency -- a multi-question problem
• Question 111 - Filtering student information with Pandas, revisited
• Question 112 - eCommerce Margins
• Question 113 - Students in a class
• Question 114 - Reorder an array by x elements in Python
• Question 115 - Binning employee experience levels in Python (Pandas)
• Question 116 - ???
• Question 117 - ???
• Question 118 - ???
• Question 119 - Chipotle item analysis (part 2)
• Question 120 - Student GPA by subject
• Question 121 - Rainy flights
• Question 122 - Middle matrix sums
• Question 123 - Normalizing student grades with Pandas, revisited
• Question 124 - Monthly revenue growth in SQL for Online channel
• Question 125 - Pricing a life insurance product
• Question 126 - Check whether two arrays are equal
• Question 127 - Animal classification with python
• Question 128 - Adult animal weights
• Question 129 - Biased coin toss
• Question 130 - Pythagorean triplet
• Question 131 - Candy production increase
• Question 132 - Querying San Francisco public worker salaries
• Question 133 - Second price (Vickrey) auction
• Question 134 - Arrays of arrays
• Question 135 - Volume weighted price average (VWAP)
• Question 136 - Chocolate Bar Reviews
• Question 137 - Auto component quality
• Question 138 - Length of largest contiguous array
• Question 139 - Plotting daily earnings (given balances)
• Question 140 - Top Earners
• Question 141 - One Way ANOVA
• Question 142 - Smallest subarray with a sum greater than X
• Question 143 - Formatting dirty data
• Question 144 - Formatting dirty data (continued)
• Question 145 - Similarity Matrix and Heat Chart
• Question 146 - Smallest, unrepresented integer
• Question 147 - Filtering strings in Pandas dataframes
• Question 148 - Filtering grades based on city avg, in SQL
• Question 149 - Testing impact of exercise on memory
• Question 150 - Multiply array values, return the remainder
• Question 151 - PCA, Inertia, and Silhouette Plots
• Question 152 - Clustering function
• Question 153 - Calculating quarterly moving average of revenue in SQL
• Question 154 - MSE vs RMSE
• Question 155 - Calculating max distance between array elements in Python
• Question 156 - World Leader Exits
• Question 157 - Company acquisitions
• Question 158 - Ads in a newsfeed
• Question 159 - Monotonic array
• Question 160 - Leader life expectancy
• Question 161 - A hotel chain's loyal customers
• Question 162 - Overfitting vs. underfitting
• Question 163 - Counting the distance between words in Python
• Question 164 - Cereal ratings
• Question 165 - College interview results
• Question 166 - Cereal ratings: top 3 variables
• Question 167 - Identity Matrix