Complete the following Lodash exercises. The goal is to become really good at
functional programming paradigm (e.g., _.map, _.filter, _.all, _.any ...etc) and
a number of really useful Lodash methods (e.g., _.find, _.pluck ... etc).
solution blockfor/while loop is allowedFamiliarity with programming in this way will not only make you a super productive programmer but also will pave the way for you to learn MapReduce and MongoDB.
[{name: 'John'}, {name: 'Mary'}, {name: 'Joe'}, {name: 'Ben'}]4
4
return data.length[{name: 'John'}, {name: 'Mary'}, {name: 'Joe'}, {name: 'Ben'}][ "John", "Mary", "Joe", "Ben" ]
[ "John", "Mary", "Joe", "Ben" ]
return _.map(data, function(d){ return d.name })
[{name: 'John'}, {name: 'Mary'}, {name: 'Joe'}, {name: 'Ben'}][ "John", "Joe" ]
[ "John", "Joe" ]
return _.filter(_.pluck(data, 'name'), function(d){ return d.match(/J.*/) })
[{name: 'John'}, {name: 'John'}, {name: 'John'}, {name: 'Ben'}]3
3
return _.size(_.filter(data, function(n){ return n.name == 'John' }))
[{name: 'John Smith'}, {name: 'Mary Kay'}, {name: 'Peter Pan'}, {name: 'Ben Franklin'}][ "John", "Mary", "Peter", "Ben" ]
[ "John", "Mary", "Peter", "Ben" ]
return _.map(data, function(d) { return d["name"].split(" ")[0] })
[{name: 'John Smith'}, {name: 'Mary Smith'}, {name: 'Peter Pan'}, {name: 'Ben Smith'}][ "John", "Mary", "Ben" ]
[ "John", "Mary", "Ben" ]
var smiths = _.filter(data, function(d){ return d["name"].match(/.*Smith/) }) return _.map(smiths, function(s){ return s["name"].split(" ")[0] })
[{name: 'John Smith'}, {name: 'Mary Kay'}, {name: 'Peter Pan'}][
{
"name": "Smith, John"
},
{
"name": "Kay, Mary"
},
{
"name": "Pan, Peter"
}
][
{
"name": "Smith, John"
},
{
"name": "Kay, Mary"
},
{
"name": "Pan, Peter"
}
]return _.chain(data) .map(function(d) { var n = d["name"].split(" "); return {"name": n[1] + ', ' + n[0]}; })
[{name: 'John Smith', gender: 'm'}, {name: 'Mary Smith', gender: 'f'}, {name: 'Peter Pan', gender: 'm'}, {name: 'Ben Smith', gender: 'm'}]1
1
return _.size(_.filter(data, function(d){ return d.gender == 'f' }))
[{name: 'John Smith', gender: 'm'}, {name: 'Mary Smith', gender: 'f'}, {name: 'Peter Pan', gender: 'm'}, {name: 'Ben Smith', gender: 'm'}]2
2
var men = _.filter(data, function(d){ return d["gender"] == 'm' }) return _.size(_.filter(men, function(m){ return m["name"].split(" ")[1] == "Smith" }))
[{name: 'John Smith', gender: 'm'}, {name: 'Mary Smith', gender: 'f'}, {name: 'Peter Pan', gender: 'm'}, {name: 'Ben Smith', gender: 'm'}]true
true
var men = _.size(_.filter(data, function(d){ return d.gender == 'm' })) var women = _.size(_.filter(data, function(d){ return d.gender == 'f' })) return (men > women)
[{name: 'John Smith', gender: 'm'}, {name: 'Mary Smith', gender: 'f'}, {name: 'Peter Pan', gender: 'm'}, {name: 'Ben Smith', gender: 'm'}]"m"
"m"
return _.filter(data, function(d){ return d["name"] == "Peter Pan" })[0].gender
[{name: 'John Smith', age: 54}, {name: 'Mary Smith', age: 42}, {name: 'Peter Pan', age: 15}, {name: 'Ben Smith', age: 35}]54
54
return _.max(_.pluck(data, 'age'))
[{name: 'John Smith', age: 54}, {name: 'Mary Smith', age: 42}, {name: 'Peter Pan', age: 15}, {name: 'Ben Smith', age: 35}]true
true
var size = data.length var l60 = _.size(_.filter(data, function(d){ return d["age"] < 60 })) return (size == l60)
[{name: 'John Smith', age: 54}, {name: 'Mary Smith', age: 42}, {name: 'Peter Pan', age: 15}, {name: 'Ben Smith', age: 35}]true
true
return _.size(_.filter(data, function(d){ return d["age"] < 18 })) > 0
[{name: 'John Smith', age: 54, favorites: ['food', 'movies']},
{name: 'Mary Smith', age: 42, favorites: ['food', 'travel']},
{name: 'Peter Pan', age: 15, favorites: ['minecraft', 'pokemo']},
{name: 'Ben Smith', age: 35, favorites: ['craft', 'food']}]3
3
return _.size(_.filter(_.pluck(data, "favorites"), function(f){ return f[0] == "food" || f[1] == "food" }))
[{name: 'John Smith', age: 54, favorites: ['food', 'movies']},
{name: 'Mary Smith', age: 42, favorites: ['food', 'travel']},
{name: 'Peter Pan', age: 15, favorites: ['minecraft', 'pokemo']},
{name: 'Joe Johnson', age: 46, favorites: ['travel', 'movies']},
{name: 'Ben Smith', age: 35, favorites: ['craft', 'food']}][ "Mary Smith", "Joe Johnson" ]
[ "Mary Smith", "Joe Johnson" ]
var age = _.filter(data, function(d){ return d["age"] > 40 }) return _.pluck(_.filter(age, function(a){ return a["favorites"][0] == 'travel' || a["favorites"][1] == 'travel' }), "name")
[{name: 'John Smith', age: 54, favorites: ['food', 'movies']},
{name: 'Mary Smith', age: 42, favorites: ['food', 'travel']},
{name: 'Peter Pan', age: 15, favorites: ['minecraft', 'pokemo']},
{name: 'Joe Johnson', age: 46, favorites: ['travel', 'movies']},
{name: 'Ben Smith', age: 35, favorites: ['craft', 'food']}]"John Smith"
"John Smith"
var food = _.filter(data, function(d){ return d["favorites"][0] == "food" || d["favorites"][1] == "food" }) return _.last(_.pluck(_.sortBy(food, "age"), "name"))
[{name: 'John Smith', age: 54, favorites: ['food', 'movies']},
{name: 'Mary Smith', age: 42, favorites: ['food', 'travel']},
{name: 'Peter Pan', age: 15, favorites: ['minecraft', 'pokemo']},
{name: 'Joe Johnson', age: 46, favorites: ['travel', 'movies']},
{name: 'Ben Smith', age: 35, favorites: ['craft', 'food']}][ "food", "movies", "travel", "minecraft", "pokemo", "craft" ]
[ "food", "movies", "travel", "minecraft", "pokemo", "craft" ]
// hint: use _.pluck, _.uniq, _.flatten in some order return _.uniq(_.flatten(_.pluck(data, 'favorites')))
[{name: 'John Smith', age: 54, favorites: ['food', 'movies']},
{name: 'Mary Smith', age: 42, favorites: ['food', 'travel']},
{name: 'Peter Pan', age: 15, favorites: ['minecraft', 'pokemo']},
{name: 'Joe Johnson', age: 46, favorites: ['travel', 'movies']},
{name: 'Ben Smith', age: 35, favorites: ['craft', 'food']}][ "Smith", "Pan", "Johnson" ]
[ "Smith", "Pan", "Johnson" ]
return _.uniq(_.map(data, function(d) { return d["name"].split(" ")[1] }))