Working towards my Data Science interviews.

Hey y’all,

After all my work at UC Berkeley, I’m now seriously considering pursuing a job as an entry-level data analyst.

I spoke to my friend, worked closely with mentors, and confided in counselors about the gruesome and hard work I feel is ahead of me.

Yet, I realize that I am fully capable of obtaining this entry-level Data Science JOB. CAN YOU BELIEVE I thought I didn’t have what it takes to even apply for a DATA SCIENCE JOB?!

I can’t believe it either.

Right now I’m stressed, and I started jumping to conclusions that I didn’t have the guts, skills or experience to compete in the field of work. I didn’t believe in myself. However, I didn’t stop there; I complained and talked to friends (legit friends who ‘made it’). My friends uplifted me, encouraged me, and pushed me to try my best. They told me things I didn’t believe, like, I am so smart, I am going to be rich, I am a friend to savor (they didn’t say savor, but I can’t think of the right word rn). Then eventually I started believing these things.

I really thought this time was so debilitating because I’ve heard stories of people applying to 150 applications to hear back from 1 or 3 interviews.

I am very grateful for my support system, and as I continue to ‘advocate’ for myself even if it’s in the form of defeat, and as if I felt like I didn’t have what it takes to be a Data Scientist.

I slowly learned that I am qualified. I am the perfect candidate, and I deserve this job position.

Sometimes I can get really bogged down, and that’s why I have friends!

I am super happy today, and I had sad dark days behind me, but now I look forward to this challenge, and I feel prepared to take this on head-on. Now starting with StrataScratch.

I GOT THIS.

I remember my baby days where I couldn’t understand abstract like general thinking about data, and I JUST WANTED THE CODE DESPERATELY because everything was too painful. Now I can understand a break down of it without having the code because I can understand the overall structure. Like here is what I asked CHAT:

hey chat I’m practicing for data science entry level interviews and I need your help explaining what is the next step I should take since I am not familiar with merging two tables and here I am challenged with this new exercise, can you help me reach this next goal given what I’ve already coded and what the question asks for. I will send the question then I want you to tell me the order of execution I should think of:

CHAT’s ANSWER: hehehe I’m so happy! So strange to be happy over data >.<

To tackle this task efficiently, you can follow these steps:

1. **Understand the Data**: Review the structure and contents of both the `entertainment_catalog` and `flight_schedule` tables. Ensure you understand the columns and their meanings.

2. **Filter Relevant Flights**: Begin by filtering the `flight_schedule` table to retrieve the flight information for flight 101. You’ll need the flight’s duration for further processing.

3. **Filter Suitable Movies**: Next, filter the `entertainment_catalog` table to find movies whose duration is less than or equal to the flight’s duration obtained in the previous step. You’ll be matching the duration of each movie with the flight’s duration.

4. **Join Tables**: Merge or join the filtered flight data with the filtered movie data based on the condition that the movie’s duration is less than or equal to the flight’s duration.

5. **Select Desired Columns**: After joining the tables, select the relevant columns from the resulting dataset. In this case, you need ‘flight_id’, ‘movie_id’, and ‘movie_duration’.

6. **Output Formatting**: Ensure the output is formatted according to the expected output, with each row containing the flight ID, movie ID, and movie duration for the suggested movies.

Here’s the order of execution in summary:
1. Understand the data.
2. Filter relevant flights.
3. Filter suitable movies.
4. Join tables based on duration.
5. Select desired columns.
6. Format the output.

By following these steps, you should be able to develop the feature as per the given challenge. Let me know if you need further assistance with any specific step!