The recommender will give you 3 names that you might like according to you own input.
nat2022.csv: https://www.insee.fr/fr/statistiques/7633685?sommaire=7635552
names_per_year.csv: list of names and many features (see Features below)
names.csv: dataset I used to do the prepare Tableau presentation
data_tableau3.csv: re-arranged data from names_per_year.csv to use it in Tableau
nat2022.csv: (original dataset) list of name per year and the number of time it is given for the given year.
Babys_names_DATA: the notebook with cleaned data and where features (from calculations and web scraping) were added
Baby_names_MODEL: the notebook where the model and the recommender are build
Baby_names_TABLEAU: the notebook were the data are build to fit in Tableau
Given_total = the number of times the name was given
Given_since2013 = total count since 2013
Given_since2018 = total count since 2013
Given_2013yn = if the name appears at least once since 2013
Given_2018yn = if the name appears at least once since 2018
Popularity_10y = % evolution since 2013
Popularity_5y = % evolution since 2018
Decade = the decade the name was the most popular (1900-1910=1900s ; 1910-1920=1910s ; ... ; 2010-2022= since 2010)
Lenght = length of the names
Neutral = find same names given for gender=F and gender=M
Hyphen = names with hyphen (1=yes ; 0=no)
Count = how many years the name was given at least once
Category = names are put into same sized bins (Very Popular, Popular, Common, Uncommon, Rare, Very rare)
Flower_names = 1 or 0 is the names is from a flower or related to nature
10 Origin features (origin_names) = 1 or 0 (origin=arabic, greek, turkish, american, english, french, italian, latin, celt, germanic)
Biblic_names = 1 or 0
Viking_names = 1 or 0
Mythology_names = 1 or 0
Fiction_names = 1 or 0 (grouped together disney names, heros names, fairy names)
https://public.tableau.com/app/profile/cyrielle.mary/viz/End-Project2/evolmixed?publish=yes
https://docs.google.com/presentation/d/1xSQdHUB5vU8_BC79FR78y3M1EkUtxlx7ondPLuQd8zI/
The recommender works as the following:
1- ask for input genre: "boy or girl?"
2- ask for input name: what name do you like ?
3- if input name in names_cluster DF == F
3a- search the cluster of input name
3b- give a recommandation from the same cluster
4- input question: do you like the name?
4a- if yes, give another name from the same cluster
4b- if no, give a name from another cluster
5- input question: do you like the name?
5a- if yes, give another name from the same cluster
5b- if no, give a name from another cluster
6- if input name in names_cluster DF == M
6a- search the cluster of input name
6b- give a recommandation from the same cluster
7- input question: do you like the name?
7a- if yes, give another name from the same cluster
7b- if no, give a name from another cluster
8- input question: do you like the name?
8a- if yes, give another name from the same cluster
8b- if no, give a name from another cluster
Are you looking for a recommandation for a girl or a boy? Please enter girl or boy: girl
Enter a name you like: CARLA
Our recommendation is AMEL.
Do you like this name? please answer yes or no: YES
Our next recommendation is HÉLOÏSE.
Do you like this name? please answer yes or no: NO
Our last recommendation is PRISCA. Thank you for using our recommender