FT_RMT_2408_ES David Carballo

README.md

@@ -23,7 +23,8 @@ $ git commit -m "done"
 $ git push origin master
 ```
 
-- Create Pull Request so your TAs can check up your work.
+- Create a Pull Request and submit your assignment.
+
 
 ## Deliverables
 
@@ -51,44 +52,199 @@ The database contains more than 18k documents. Each document holds the data abou
 
 1. You will find the `.zip` file of the database on the **lab** folder.
 2. Unzip the file
-3. Navigate to this lab's folder in your terminal, and when inside, import the database to Mongo using the following command:
+3. Open MongoDB Compass and connect to your MongoDB server.
+4. Create a new database named `companiesDB` and inside of it a collection  named `companies`.
+5. Import the data from the .json file in to the collection `companies`.
+6. Check on MongoDB Compass if everything goes ok:
 
-**When running the `mongoimport` you should be located in the same folder as the `data.json` file.**
+![image](https://user-images.githubusercontent.com/23629340/36534191-1f1bc5ec-17c6-11e8-9463-4945679b98c0.png)
 
-```bash
-$ mongoimport --db companiesDB --collection companies --file data.json
-```
+### Iteration 2
 
-What this mongoimport will do for us is to create a database named _companiesDB_, and inside the database will create a collection named _companies_ which will be fed with _data.json_.
+You already know how this goes, so let's start working:
 
-_Side note_: In case errors or hanging with no response when running this command, add [--jsonArray](https://docs.mongodb.com/manual/reference/program/mongoimport/#cmdoption-mongoimport-jsonarray) at the end of the previous command.
+1. All the companies whose name match 'Babelgum'. Retrieve only their `name` field.
 
-4. Check on Mongo Compass if everything goes ok:
+<details>
+  <summary>Solution</summary>
 
-![image](https://user-images.githubusercontent.com/23629340/36534191-1f1bc5ec-17c6-11e8-9463-4945679b98c0.png)
+- Query: `{name: 'Babelgum'}`
+- Projection: `{name: 1, _id: 0}`
 
-### Iteration 2
+</details>
 
-You already know how this goes, so let's start working:
+<br>
 
-1. All the companies whose name match 'Babelgum'. Retrieve only their `name` field.
 2. All the companies that have more than 5000 employees. Limit the search to 20 companies and sort them by **number of employees**.
+
+<details>
+  <summary>Solution</summary>
+
+- Query: `{number_of_employees: { $gt: 5000 }}`
+- Limit: `20`
+
+</details>
+
+<br>
+
 3. All the companies founded between 2000 and 2005, both years included. Retrieve only the `name` and `founded_year` fields.
-4. All the companies that had a IPO Valuation Amount of more than 100.000.000 and have been founded before 2010. Retrieve only the `name` and `ipo` fields.
-5. All the companies that have less than 1000 employees and have been founded before 2005. Order them by the number of employees and limit the search to 10 companies.
-6. All the companies that don't include the `partners` field.
-7. All the companies that have a null type of value on the `category_code` field.
-8. All the companies that have at least 100 employees but less than 1000. Retrieve only the `name` and `number of employees` fields.
-9. Order all the companies by their IPO price in descending order.
-10. Retrieve the ten companies with most employees, order by the `number of employees`
-11. All the companies founded in the second semester of the year. Limit your search to 1000 companies.
-12. All the companies founded before 2000 that have an acquisition amount of more than 10.000.000
-13. All the companies that have been acquired after 2010, order by the acquisition amount, and retrieve only their `name` and `acquisition` field.
-14. Order the companies by their `founded year`, retrieving only their `name` and `founded year`.
-15. All the companies that have been founded on the first seven days of the month, including the seventh. Sort them by their `acquisition price` in descending order. Limit the search to 10 documents.
-16. All the companies on the 'web' `category` that have more than 4000 employees. Sort them by the number of employees in ascending order.
-17. All the companies whose acquisition amount is more than 10.000.000 and the currency is 'EUR'.
-18. All the companies that have been acquired in the first trimester of the year. Limit the search to 10 companies, and retrieve only their `name` and `acquisition` fields.
-19. All the companies that have been founded between 2000 and 2010, but have not been acquired before 2011.
+
+<details>
+  <summary>Solution</summary>
+
+- Query: `{$and: [{founded_year: {$gte: 2000}}, {founded_year:{$lte: 2005}}]}`
+- Projection: `{name: 1, _id: 0, founded_year: 1}`
+
+</details>
+
+<br>
+
+4. All the companies that had a IPO Valuation Amount of more than 100,000,000 and have been founded before 2010. Retrieve only the `name` and `ipo` fields.
+
+<details>
+  <summary>Solution</summary>
+
+- Query: `{$and: [{'ipo.valuation_amount': {$gte: 10000000}}, {founded_year:{$lt: 2010}}]}`
+    - Shorthand: `{founded_year: {$lt:2010}, "ipo.valuation_amount": {$gt: 100000000}}`
+- Projection: `{name: 1, _id: 0, ipo: 1}`
+
+</details>
+
+<br>
+
+5. All the companies that don't include the `partners` field.
+
+<details>
+  <summary>Solution</summary>
+
+- Query: `{partners: {$exists: false}}`
+
+</details>
+
+<br>
+
+6. All the companies that have a null type of value on the `category_code` field.
+
+<details>
+  <summary>Solution</summary>
+
+- Query: `{category_code: {$type: 'null'}}`
+
+</details>
+
+<br>
+
+7. Order all the companies by their IPO price in descending order.
+
+<details>
+  <summary>Solution</summary>
+
+- Sort: `{'ipo.valuation_amount': -1}`
+
+</details>
+
+<br>
+
+8. Retrieve the 10 companies with the most employees, order by the `number of employees`.
+
+<details>
+  <summary>Solution</summary>
+
+- Query: `{ number_of_employees: { $exists: true } }`
+- Sort:  `{number_of_employees: -1}`
+- Limit: `10`
+
+</details>
+
+<br>
+
+9. All the companies founded in the second semester of the year (July to December). Limit your search to 1000 companies.
+
+<details>
+  <summary>Solution</summary>
+
+- Query: `{founded_month: {$gte: 7}}`
+- Limit: `1000`
+
+</details>
+
+<br>
+
+10. All the companies that have been founded on the first seven days of the month, including the seventh. Sort them by their `acquisition price` in descending order. Limit the search to 10 documents.
+
+<details>
+  <summary>Solution</summary>
+
+- Query: `{founded_day: {$lte: 7}}`
+- Sort: `{'acquisition.price_amount': -1}`
+- Limit: `10`
+
+</details>
+
+<br>
+
+### Iteration 3 (Bonus)
+
+For an extra challenge and additional practice, try the following queries:
+
+1. All the companies that have been acquired after 2010, order by the acquisition amount, and retrieve only their `name` and `acquisition` field.
+
+<details>
+  <summary>Solution</summary>
+
+- Query: `{'acquisition.acquired_year': {$gt: 2010}}`
+- Projection: `{name: 1, acquisition: 1, _id: 0}`
+- Sort: `{'acquisition.price_amount': -1}`
+
+</details>
+
+<br>
+
+2. Order the companies by their `founded year`, retrieving only their `name` and `founded year`.
+
+<details>
+  <summary>Solution</summary>
+
+- Query: `{'founded_year': { '$ne': null }}`
+- Projection: `{name: 1, founded_year: 1, _id: 0}`
+- Sort: `{founded_year: 1}`
+
+</details>
+
+<br>
+
+3. All the companies on the 'web' `category` that have more than 4000 employees. Sort them by the number of employees in ascending order.
+
+<details>
+  <summary>Solution</summary>
+
+- Query: `{$and: [{category_code: 'web'}, {number_of_employees: {$gt: 4000}}]}`
+- Sort: `{number_of_employees: 1}`
+
+</details>
+
+<br>
+
+4. All the companies whose acquisition amount is more than 10,000,000 and the currency is 'EUR'.
+
+<details>
+  <summary>Solution</summary>
+
+- Query: `{$and: [{'acquisition.price_currency_code': 'EUR'}, {'acquisition.price_amount': {$gt: 10000000}}]}`
+
+</details>
+
+<br>
+
+5. All the companies that have been founded between 2000 and 2010, but have not been acquired before 2011.
+
+<details>
+  <summary>Solution</summary>
+
+- Query: `{$and: [{founded_year: {$gte: 2000}}, {founded_year: {$lte: 2010}}, {'acquisition.acquired_year':{$gt:2011}}]}`
+
+</details>
+
+<br>
 
 Happy Coding! :heart: