Skip to content

Commit 16fc60d

Browse files
joeyajamesjoeyajames
authored
Python Lambda Functions Jupyter initial upload
1 parent b6cb971 commit 16fc60d

File tree

1 file changed

+364
-0
lines changed

1 file changed

+364
-0
lines changed

‎Numpy/Lambda Functions/Python Lambda Functions.ipynb

Lines changed: 364 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,364 @@
1+
{
2+
"cells": [
3+
{
4+
"cell_type": "markdown",
5+
"metadata": {},
6+
"source": [
7+
"# Python Lambda Functions\n",
8+
"Anonymous, single-use, or throw-away functions. \n",
9+
"**lambda arguments : expression** \n",
10+
"Here are some single-argument lambdas:"
11+
]
12+
},
13+
{
14+
"cell_type": "code",
15+
"execution_count": 59,
16+
"metadata": {},
17+
"outputs": [
18+
{
19+
"name": "stdout",
20+
"output_type": "stream",
21+
"text": [
22+
"12\n"
23+
]
24+
}
25+
],
26+
"source": [
27+
"add5 = lambda x: x + 5\n",
28+
"print(add5(7))"
29+
]
30+
},
31+
{
32+
"cell_type": "code",
33+
"execution_count": 58,
34+
"metadata": {},
35+
"outputs": [
36+
{
37+
"name": "stdout",
38+
"output_type": "stream",
39+
"text": [
40+
"64\n"
41+
]
42+
}
43+
],
44+
"source": [
45+
"square = lambda x: x * x\n",
46+
"print(square(8))"
47+
]
48+
},
49+
{
50+
"cell_type": "code",
51+
"execution_count": 67,
52+
"metadata": {},
53+
"outputs": [
54+
{
55+
"name": "stdout",
56+
"output_type": "stream",
57+
"text": [
58+
"4\n",
59+
"3\n"
60+
]
61+
}
62+
],
63+
"source": [
64+
"get_tens = lambda p: int(p/10)%10\n",
65+
"print(get_tens(749))\n",
66+
"print(get_tens(836.21))"
67+
]
68+
},
69+
{
70+
"cell_type": "markdown",
71+
"metadata": {},
72+
"source": [
73+
"**Lambdas as an argument in other functions** \n",
74+
"One of the most popular uses for lambda functions is as an argument inside sort, or filter functions. \n",
75+
"### Sorting a List of Tuples using Lambda"
76+
]
77+
},
78+
{
79+
"cell_type": "code",
80+
"execution_count": 80,
81+
"metadata": {},
82+
"outputs": [
83+
{
84+
"name": "stdout",
85+
"output_type": "stream",
86+
"text": [
87+
"[('carrots', 1.1), ('peaches', 2.45), ('eggs', 5.25), ('honey', 9.7)]\n"
88+
]
89+
}
90+
],
91+
"source": [
92+
"list1 = [('eggs', 5.25), ('honey', 9.70), ('carrots', 1.10), ('peaches', 2.45)]\n",
93+
"list1.sort(key = lambda x: x[1])\n",
94+
"print(list1)"
95+
]
96+
},
97+
{
98+
"cell_type": "markdown",
99+
"metadata": {},
100+
"source": [
101+
"### Sorting a List of Dictionaries using Lambda"
102+
]
103+
},
104+
{
105+
"cell_type": "code",
106+
"execution_count": 63,
107+
"metadata": {},
108+
"outputs": [
109+
{
110+
"name": "stdout",
111+
"output_type": "stream",
112+
"text": [
113+
"[{'make': 'Tesla', 'model': 'X', 'year': 1999},\n",
114+
" {'make': 'Mercedes', 'model': 'C350E', 'year': 2008},\n",
115+
" {'make': 'Ford', 'model': 'Focus', 'year': 2013}]\n"
116+
]
117+
}
118+
],
119+
"source": [
120+
"import pprint as pp\n",
121+
"list1 = [{'make':'Ford', 'model':'Focus', 'year':2013}, {'make':'Tesla', 'model':'X', 'year':1999}, {'make':'Mercedes', 'model':'C350E', 'year':2008}]\n",
122+
"list2 = sorted(list1, key = lambda x: x['year'])\n",
123+
"pp.pprint(list2)"
124+
]
125+
},
126+
{
127+
"cell_type": "markdown",
128+
"metadata": {},
129+
"source": [
130+
"### Filtering a List of Integers using Lambda"
131+
]
132+
},
133+
{
134+
"cell_type": "code",
135+
"execution_count": 64,
136+
"metadata": {},
137+
"outputs": [
138+
{
139+
"name": "stdout",
140+
"output_type": "stream",
141+
"text": [
142+
"[2, 4, 6]\n"
143+
]
144+
}
145+
],
146+
"source": [
147+
"list1 = [1, 2, 3, 4, 5, 6]\n",
148+
"list2 = list(filter(lambda x: x%2 == 0, list1))\n",
149+
"print(list2)"
150+
]
151+
},
152+
{
153+
"cell_type": "code",
154+
"execution_count": 49,
155+
"metadata": {},
156+
"outputs": [
157+
{
158+
"name": "stdout",
159+
"output_type": "stream",
160+
"text": [
161+
"[1, 3, 5]\n"
162+
]
163+
}
164+
],
165+
"source": [
166+
"odds = lambda x: x%2 == 1\n",
167+
"list1 = [1, 2, 3, 4, 5, 6]\n",
168+
"list2 = list(filter(odds, list1))\n",
169+
"print(list2)"
170+
]
171+
},
172+
{
173+
"cell_type": "markdown",
174+
"metadata": {},
175+
"source": [
176+
"### Lambda Function on a List using Map\n",
177+
"Python's map function applies the lambda to every element in the list."
178+
]
179+
},
180+
{
181+
"cell_type": "code",
182+
"execution_count": 74,
183+
"metadata": {},
184+
"outputs": [
185+
{
186+
"name": "stdout",
187+
"output_type": "stream",
188+
"text": [
189+
"[1, 4, 9, 16, 25, 36]\n"
190+
]
191+
}
192+
],
193+
"source": [
194+
"list1 = [1, 2, 3, 4, 5, 6]\n",
195+
"list2 = list(map(lambda x: x ** 2, list1))\n",
196+
"print(list2)"
197+
]
198+
},
199+
{
200+
"cell_type": "markdown",
201+
"metadata": {},
202+
"source": [
203+
"### Lambda Conditionals\n",
204+
"**lambda args: a if boolean_expression else b** "
205+
]
206+
},
207+
{
208+
"cell_type": "code",
209+
"execution_count": 70,
210+
"metadata": {},
211+
"outputs": [
212+
{
213+
"name": "stdout",
214+
"output_type": "stream",
215+
"text": [
216+
"True\n"
217+
]
218+
}
219+
],
220+
"source": [
221+
"starts_with_J = lambda x: True if x.startswith('J') else False\n",
222+
"print(starts_with_J('Joey'))"
223+
]
224+
},
225+
{
226+
"cell_type": "code",
227+
"execution_count": 81,
228+
"metadata": {},
229+
"outputs": [
230+
{
231+
"name": "stdout",
232+
"output_type": "stream",
233+
"text": [
234+
"and\n"
235+
]
236+
}
237+
],
238+
"source": [
239+
"wordb4 = lambda s, w: s.split()[s.split().index(w)-1] if w in s else None\n",
240+
"sentence = 'Four score and seven years ago'\n",
241+
"print(wordb4(sentence, 'seven'))"
242+
]
243+
},
244+
{
245+
"cell_type": "markdown",
246+
"metadata": {},
247+
"source": [
248+
"### Lambdas on DataTime Objects\n",
249+
"You sometimes want to get just the year, month, date or time for comparision. \n",
250+
"This would typically be most useful as a parameter in sort or filter functions."
251+
]
252+
},
253+
{
254+
"cell_type": "code",
255+
"execution_count": 82,
256+
"metadata": {},
257+
"outputs": [
258+
{
259+
"name": "stdout",
260+
"output_type": "stream",
261+
"text": [
262+
"2019-03-07 19:36:58.442863\n",
263+
"2019\n"
264+
]
265+
}
266+
],
267+
"source": [
268+
"import datetime\n",
269+
"\n",
270+
"now = datetime.datetime.now()\n",
271+
"print(now)\n",
272+
"year = lambda x: x.year\n",
273+
"print(year(now))"
274+
]
275+
},
276+
{
277+
"cell_type": "code",
278+
"execution_count": 79,
279+
"metadata": {},
280+
"outputs": [
281+
{
282+
"name": "stdout",
283+
"output_type": "stream",
284+
"text": [
285+
"4096\n",
286+
"125\n"
287+
]
288+
}
289+
],
290+
"source": [
291+
"def do_something(f, val):\n",
292+
" return f(val)\n",
293+
"\n",
294+
"func = lambda x: x**3\n",
295+
"print(func(16))\n",
296+
"print(do_something(func, 5))"
297+
]
298+
},
299+
{
300+
"cell_type": "markdown",
301+
"metadata": {},
302+
"source": [
303+
"### Extreme Lambdas\n",
304+
"This is probably a stretch -- you shouldn't be trying to do this much with Lambdas. \n",
305+
"Some things are better done in a regular function. But this shows what's possible with Lambdas."
306+
]
307+
},
308+
{
309+
"cell_type": "code",
310+
"execution_count": 66,
311+
"metadata": {},
312+
"outputs": [
313+
{
314+
"name": "stdout",
315+
"output_type": "stream",
316+
"text": [
317+
"True\n",
318+
"True\n",
319+
"False\n",
320+
"False\n",
321+
"True\n",
322+
"-1\n",
323+
"-21.67 <class 'float'>\n"
324+
]
325+
}
326+
],
327+
"source": [
328+
"isnum = lambda q: q.replace('.','',1).isdigit()\n",
329+
"print(isnum('25983'))\n",
330+
"print(isnum('3.1415'))\n",
331+
"print(isnum('T57'))\n",
332+
"print(isnum('-16'))\n",
333+
"\n",
334+
"is_num = lambda r: isnum(r[1:]) if r[0]=='-' else isnum(r)\n",
335+
"print(is_num('-16.4'))\n",
336+
"\n",
337+
"tonum = lambda s: float(s) if is_num(s) else -1\n",
338+
"print(tonum('30y'))\n",
339+
"print(tonum('-21.67'), type(tonum('-21.67')))"
340+
]
341+
}
342+
],
343+
"metadata": {
344+
"kernelspec": {
345+
"display_name": "Python 3",
346+
"language": "python",
347+
"name": "python3"
348+
},
349+
"language_info": {
350+
"codemirror_mode": {
351+
"name": "ipython",
352+
"version": 3
353+
},
354+
"file_extension": ".py",
355+
"mimetype": "text/x-python",
356+
"name": "python",
357+
"nbconvert_exporter": "python",
358+
"pygments_lexer": "ipython3",
359+
"version": "3.7.0"
360+
}
361+
},
362+
"nbformat": 4,
363+
"nbformat_minor": 2
364+
}

0 commit comments

Comments
 (0)