Skip to content

Commit 02522de

Browse files
author
Abdullah-Niaz
committed
python problems
1 parent f8bdede commit 02522de

File tree

12 files changed

+1838
-83
lines changed

12 files changed

+1838
-83
lines changed

‎Lession 1 Intorduction of python Programming/.ipynb_checkpoints/Untitled-checkpoint.ipynb renamed to ‎.ipynb_checkpoints/Data Analysis with Python Introduction-checkpoint.ipynb

File renamed without changes.

‎Data Analysis with Python Introduction.ipynb

+306
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,306 @@
1+
{
2+
"cells": [
3+
{
4+
"cell_type": "code",
5+
"execution_count": 8,
6+
"id": "1943560c",
7+
"metadata": {},
8+
"outputs": [
9+
{
10+
"name": "stdout",
11+
"output_type": "stream",
12+
"text": [
13+
"[['a' 'b']\n",
14+
" ['d' 'e']\n",
15+
" ['g' 'h']]\n"
16+
]
17+
}
18+
],
19+
"source": [
20+
"import numpy as np\n",
21+
"A = np.array([\n",
22+
" ['a', 'b', 'c'],\n",
23+
" ['d', 'e', 'f'],\n",
24+
" ['g', 'h', 'i']\n",
25+
"])\n",
26+
"\n",
27+
"print(A[:, : 2])\n",
28+
"# because (rows and columns )\n"
29+
]
30+
},
31+
{
32+
"cell_type": "code",
33+
"execution_count": 12,
34+
"id": "bb3f9279",
35+
"metadata": {},
36+
"outputs": [
37+
{
38+
"data": {
39+
"text/plain": [
40+
"array([20, 21, 22, 23, 24])"
41+
]
42+
},
43+
"execution_count": 12,
44+
"metadata": {},
45+
"output_type": "execute_result"
46+
}
47+
],
48+
"source": [
49+
"a = np.arange(5)\n",
50+
"a + 20\n",
51+
"# it will be added with the every index of array"
52+
]
53+
},
54+
{
55+
"cell_type": "code",
56+
"execution_count": 14,
57+
"id": "b2b7604f",
58+
"metadata": {},
59+
"outputs": [
60+
{
61+
"name": "stdout",
62+
"output_type": "stream",
63+
"text": [
64+
"[ True True True True False]\n"
65+
]
66+
}
67+
],
68+
"source": [
69+
"a = np.arange(5)\n",
70+
"\n",
71+
"print(a <= 3)"
72+
]
73+
},
74+
{
75+
"cell_type": "code",
76+
"execution_count": 16,
77+
"id": "030a325a",
78+
"metadata": {},
79+
"outputs": [
80+
{
81+
"name": "stdout",
82+
"output_type": "stream",
83+
"text": [
84+
"Tom 8\n",
85+
"Kris 2\n",
86+
"Ahmad 5\n",
87+
"Beau 6\n",
88+
"dtype: int64\n"
89+
]
90+
}
91+
],
92+
"source": [
93+
"import pandas as pd\n",
94+
"\n",
95+
"certificates_earned = pd.Series(\n",
96+
" [8, 2, 5, 6],\n",
97+
" index=['Tom', 'Kris', 'Ahmad', 'Beau']\n",
98+
")\n",
99+
"\n",
100+
"print(certificates_earned)"
101+
]
102+
},
103+
{
104+
"cell_type": "code",
105+
"execution_count": 18,
106+
"id": "a489afa1",
107+
"metadata": {},
108+
"outputs": [
109+
{
110+
"name": "stdout",
111+
"output_type": "stream",
112+
"text": [
113+
"Tom 8\n",
114+
"Beau 6\n",
115+
"dtype: int64\n"
116+
]
117+
}
118+
],
119+
"source": [
120+
"import pandas as pd\n",
121+
"\n",
122+
"certificates_earned = pd.Series(\n",
123+
" [8, 2, 5, 6],\n",
124+
" index=['Tom', 'Kris', 'Ahmad', 'Beau']\n",
125+
")\n",
126+
"\n",
127+
"print(certificates_earned[certificates_earned > 5])"
128+
]
129+
},
130+
{
131+
"cell_type": "code",
132+
"execution_count": 20,
133+
"id": "887f672a",
134+
"metadata": {},
135+
"outputs": [
136+
{
137+
"name": "stdout",
138+
"output_type": "stream",
139+
"text": [
140+
"Certificates 5\n",
141+
"Time (in months) 9\n",
142+
"Name: Ahmad, dtype: int64\n"
143+
]
144+
}
145+
],
146+
"source": [
147+
"import pandas as pd\n",
148+
"\n",
149+
"certificates_earned = pd.DataFrame({\n",
150+
" 'Certificates': [8, 2, 5, 6],\n",
151+
" 'Time (in months)': [16, 5, 9, 12]\n",
152+
"})\n",
153+
"\n",
154+
"certificates_earned.index = ['Tom', 'Kris', 'Ahmad', 'Beau']\n",
155+
"\n",
156+
"print(certificates_earned.iloc[2])"
157+
]
158+
},
159+
{
160+
"cell_type": "code",
161+
"execution_count": 29,
162+
"id": "decbcb66",
163+
"metadata": {},
164+
"outputs": [],
165+
"source": [
166+
"ss = pd.Series(5)"
167+
]
168+
},
169+
{
170+
"cell_type": "code",
171+
"execution_count": 31,
172+
"id": "720ba625",
173+
"metadata": {},
174+
"outputs": [
175+
{
176+
"name": "stdout",
177+
"output_type": "stream",
178+
"text": [
179+
" Certificates Time (in months) Longest streak\n",
180+
"Tom 8 16 13\n",
181+
"Kris 2 5 11\n",
182+
"Ahmad 5 9 9\n",
183+
"Beau 6 12 7\n"
184+
]
185+
}
186+
],
187+
"source": [
188+
"import pandas as pd\n",
189+
"\n",
190+
"certificates_earned = pd.DataFrame({\n",
191+
" 'Certificates': [8, 2, 5, 6],\n",
192+
" 'Time (in months)': [16, 5, 9, 12]\n",
193+
"})\n",
194+
"names = ['Tom', 'Kris', 'Ahmad', 'Beau']\n",
195+
"\n",
196+
"certificates_earned.index = names\n",
197+
"longest_streak = pd.Series([13, 11, 9, 7], index=names)\n",
198+
"certificates_earned['Longest streak'] = longest_streak\n",
199+
"\n",
200+
"print(certificates_earned)"
201+
]
202+
},
203+
{
204+
"cell_type": "code",
205+
"execution_count": 33,
206+
"id": "f0e3a2cd",
207+
"metadata": {},
208+
"outputs": [
209+
{
210+
"name": "stdout",
211+
"output_type": "stream",
212+
"text": [
213+
"3\n"
214+
]
215+
}
216+
],
217+
"source": [
218+
"import pandas as pd\n",
219+
"import numpy as np\n",
220+
"\n",
221+
"s = pd.Series(['a', 3, np.nan, 1, np.nan])\n",
222+
"\n",
223+
"print(s.notnull().sum())"
224+
]
225+
},
226+
{
227+
"cell_type": "code",
228+
"execution_count": 35,
229+
"id": "9b31141e",
230+
"metadata": {},
231+
"outputs": [
232+
{
233+
"name": "stdout",
234+
"output_type": "stream",
235+
"text": [
236+
"0 NaN\n",
237+
"1 1.0\n",
238+
"2 2.0\n",
239+
"3 2.0\n",
240+
"4 3.0\n",
241+
"dtype: float64\n"
242+
]
243+
}
244+
],
245+
"source": [
246+
"import pandas as pd\n",
247+
"import numpy as np\n",
248+
"\n",
249+
"s = pd.Series([np.nan, 1, 2, np.nan, 3])\n",
250+
"s = s.fillna(method='ffill')\n",
251+
"\n",
252+
"print(s)"
253+
]
254+
},
255+
{
256+
"cell_type": "code",
257+
"execution_count": 36,
258+
"id": "2b22ee29",
259+
"metadata": {},
260+
"outputs": [
261+
{
262+
"ename": "NameError",
263+
"evalue": "name '__A__' is not defined",
264+
"output_type": "error",
265+
"traceback": [
266+
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
267+
"\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)",
268+
"Cell \u001b[1;32mIn [36], line 3\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mcsv\u001b[39;00m\n\u001b[1;32m----> 3\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mopen\u001b[39m(\u001b[43m__A__\u001b[49m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m'\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m fp:\n\u001b[0;32m 4\u001b[0m reader \u001b[38;5;241m=\u001b[39m csv\u001b[38;5;241m.\u001b[39mreader(fp, delimiter\u001b[38;5;241m=\u001b[39m__B__)\n\u001b[0;32m 5\u001b[0m \u001b[38;5;28mnext\u001b[39m(reader)\n",
269+
"\u001b[1;31mNameError\u001b[0m: name '__A__' is not defined"
270+
]
271+
}
272+
],
273+
"source": [
274+
"import csv\n",
275+
"\n",
276+
"with open(__A__, 'r') as fp:\n",
277+
" reader = csv.reader(fp, delimiter=__B__)\n",
278+
" next(reader)\n",
279+
" for index, values in enumerate(reader):\n",
280+
" name, certs_num, months_num = values\n",
281+
" print(f\"{name} earned {__C__} certificates in {months_num} months\")"
282+
]
283+
}
284+
],
285+
"metadata": {
286+
"kernelspec": {
287+
"display_name": "Python 3 (ipykernel)",
288+
"language": "python",
289+
"name": "python3"
290+
},
291+
"language_info": {
292+
"codemirror_mode": {
293+
"name": "ipython",
294+
"version": 3
295+
},
296+
"file_extension": ".py",
297+
"mimetype": "text/x-python",
298+
"name": "python",
299+
"nbconvert_exporter": "python",
300+
"pygments_lexer": "ipython3",
301+
"version": "3.10.7"
302+
}
303+
},
304+
"nbformat": 4,
305+
"nbformat_minor": 5
306+
}

‎Intorduction - Data Analysis with python/.ipynb_checkpoints/Untitled-checkpoint.ipynb

+6
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,6 @@
1+
{
2+
"cells": [],
3+
"metadata": {},
4+
"nbformat": 4,
5+
"nbformat_minor": 5
6+
}

‎Lession 1 Intorduction of python Programming/Begginer_to_complete_.ipynb renamed to ‎Intorduction - Data Analysis with python/Begginer_to_complete_.ipynb

File renamed without changes.

‎Lession 1 Intorduction of python Programming/Find_Net_Profet.ipynb renamed to ‎Intorduction - Data Analysis with python/Find_Net_Profet.ipynb

File renamed without changes.

‎Intorduction - Data Analysis with python/What is Data Analysis.docx

11.3 KB
Binary file not shown.

‎LeetCode/fizzbuzz.ipynb

+64
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,64 @@
1+
{
2+
"cells": [
3+
{
4+
"cell_type": "code",
5+
"execution_count": 3,
6+
"metadata": {},
7+
"outputs": [
8+
{
9+
"name": "stdout",
10+
"output_type": "stream",
11+
"text": [
12+
"['1', '2', 'Fizz', '4', 'Buzz', 'Fizz', '7', '8', 'Fizz', 'Buzz', '11', 'Fizz', '13', '14', 'FizzBuzz']\n"
13+
]
14+
}
15+
],
16+
"source": [
17+
"n = 15\n",
18+
"a = []\n",
19+
"for i in range(1,n+1):\n",
20+
" if (i % 3==0):\n",
21+
" if (i % 5==0):\n",
22+
" a.append(\"FizzBuzz\")\n",
23+
" else:\n",
24+
" a.append(\"Fizz\") \n",
25+
" else:\n",
26+
" if(i%5==0):\n",
27+
" a.append(\"Buzz\")\n",
28+
" # in case if our values are not divible by 3 and 5, so append their \n",
29+
" # index to the array \n",
30+
" else:\n",
31+
" a.append(str(i))\n",
32+
" # Return the array \n",
33+
"print(a)"
34+
]
35+
}
36+
],
37+
"metadata": {
38+
"kernelspec": {
39+
"display_name": "Python 3.10.7 64-bit",
40+
"language": "python",
41+
"name": "python3"
42+
},
43+
"language_info": {
44+
"codemirror_mode": {
45+
"name": "ipython",
46+
"version": 3
47+
},
48+
"file_extension": ".py",
49+
"mimetype": "text/x-python",
50+
"name": "python",
51+
"nbconvert_exporter": "python",
52+
"pygments_lexer": "ipython3",
53+
"version": "3.10.7"
54+
},
55+
"orig_nbformat": 4,
56+
"vscode": {
57+
"interpreter": {
58+
"hash": "26de051ba29f2982a8de78e945f0abaf191376122a1563185a90213a26c5da77"
59+
}
60+
}
61+
},
62+
"nbformat": 4,
63+
"nbformat_minor": 2
64+
}

0 commit comments

Comments
 (0)