We've learned about a lot of statements we have available to us in Python to write more dynamic and concise code. Conditionals let us create conditions that inform our code how to operate. Loops help us to dynamically iterate through and operate on a collection (i.e. a list or a dictionary). And Operators, generally, allow us to compare elements to each other, assert the sameness of elements, or return elements based on their truthiness or falsiness. Functions, essentially, help us to create an object that packages up one or more operations and allows us to execute those operations from anywhere else in scope in our code. However, as we can tell by the title of this lesson, we will now be focusing on using all of these smaller parts together. As we get further into our lives as programmers, we will find ourselves facing more and more complex problems and to solve those we will need these types of tools to create solutions while keeping our code concise and efficient.

• Identify how and when to use functions, conditionals, loops, and operators
• Use functions, conditionals, loops, and operators efficiently and effectively

In this lab, we will be working with a dataset containing information from some of the largest Python-focused Meetup groups in the US. Our data is in the groups_db.py file, which we are importing below and as the variable data. You can also see an example of what the element's datastructure looks like by running the cell with data[0].

To pass the tests in this lab, create functions that perform the operations indicated and have the correct return value.

from groups import data

data[0]

Let's say we would like to have a way to find all groups in the city we're in or perhaps the city we might want to visit, to make sure we can find a python group to join.

Below, replace the pass statement with your code. The groups_in_city function takes in two arguments; the list of meetup dictionary objects, data, and a string representing a city's name. It should return only a list of dictionary's whose city attribute points to a string with the same name as the city name passed in as the second argument.

def groups_in_city(list_of_groups, city_name):
    pass

Similarly, we will probably want to make sure the groups we are looking at joining have a sizeable membership so that we have a bigger network or even a more active schedule of events.

Below, replace the pass statement with your code. The groups_with_x_members function takes in two arguments; the list of meetup dictionary objects, data, and an integer representing the minimum number of members in a group. It should return a list of dictionaries that have the same or greater number of members.

def groups_with_x_members(list_of_groups, num_members):
    pass

Another way we might want to narrow our search down for groups might be to decide how diverse of topics it covers. Maybe we might be interested in groups that have events that talk about more than just Python.

Below, replace the pass statement with your code. The groups_with_x_num_topics function takes in two arguments; the list of meetup dictionary objects, data, and an integer representing the minimum number of topics a group lists. It should return a list of dictionaries that have the same or greater number of topics listed.

def groups_with_x_num_topics(list_of_groups, num_topics):
    pass

Alright, so trying to brute force diversity of topic might have some value, but when we finally do have a group we want to take a look at, we probably want to have a way to make sure that the topics that the group lists are still actually of interest to us. So, let's create a function that will iterate through the a single group and return a list of names for each of the topics listed for that group.

Below, replace the pass statement with your code. The list_group_topics function takes in one argument, a group dictionary. It should return a list of strings that are the name of each topic for that group.

def list_group_topics(group):
    pass

Great! Now we have an easy way to check if a group has the topics we're interested in. What about just taking stock of all the groups we are currently looking at. We might want to get an idea of what the most popular topics are before we decide whether we're not interested in certain topics.

Below, replace the pass statement with your code. The find_topic_popularity function takes in one argument, the list of meetup dictionary objects, data. It should return a single dictionary that has a key for each topic listed for all groups in the list. Each key should point to the number of times that topic appears in the dataset. For example, if Python appears in 15 groups, there would be a key 'Python' that has a value of 15.

def find_topic_popularity(list_of_groups):
    pass

The previous couple functions definitely feel very useful but perhaps we actually want to be able to filter for groups that contain the topic we would like to look for.

Below, replace the pass statement with your code. The find_groups_containing_topic function takes in twp arguments; the list of meetup dictionary objects, data, and the name of the topic. It should return all groups that contain topics with a matching name.

def find_groups_containing_topic(list_of_groups, topic_name):
    pass

Okay, another, perhaps most obvious way of narrowing down our search would be to find groups above a certain rating.

Below, replace the pass statement with your code. The filter_groups_by_rating function takes in two arguments; first a list of dictionaries for each group, and second a minimum rating. The function should return a list of groups with a rating greater than or equal to the rating passed in.

def filter_groups_by_rating(list_of_groups, min_rating):
    pass

In this lab, we practiced writing functions that used conditionals, operators, and loops to select, operate on, and return the information we wanted from our dataset.