2025 0415 update
parent
4a5f06e9d1
commit
bb72e110a5
|
|
@ -18,7 +18,7 @@
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 1,
|
"execution_count": 2,
|
||||||
"id": "e9a8883a",
|
"id": "e9a8883a",
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
|
|
@ -26,22 +26,22 @@
|
||||||
"name": "stdout",
|
"name": "stdout",
|
||||||
"output_type": "stream",
|
"output_type": "stream",
|
||||||
"text": [
|
"text": [
|
||||||
"i = 1, i squared = 1\n",
|
"Value = 1, Value squared = 1\n",
|
||||||
"i = 2, i squared = 4\n",
|
"Value = 2, Value squared = 4\n",
|
||||||
"i = 3, i squared = 9\n",
|
"Value = 3, Value squared = 9\n",
|
||||||
"i = 4, i squared = 16\n",
|
"Value = 4, Value squared = 16\n",
|
||||||
"i = 5, i squared = 25\n"
|
"Value = 5, Value squared = 25\n"
|
||||||
]
|
]
|
||||||
}
|
}
|
||||||
],
|
],
|
||||||
"source": [
|
"source": [
|
||||||
"for i in [1, 2, 3, 4, 5]:\n",
|
"for dummy in [1, 2, 3, 4, 5]:\n",
|
||||||
" print(f\"i = {i}, i squared = {i**2}\")"
|
" print(f\"Value = {dummy}, Value squared = {dummy**2}\")"
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 2,
|
"execution_count": 4,
|
||||||
"id": "ee7f5f12",
|
"id": "ee7f5f12",
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
|
|
@ -60,7 +60,7 @@
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 4,
|
"execution_count": 5,
|
||||||
"id": "2667d8d8",
|
"id": "2667d8d8",
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
|
|
@ -85,7 +85,7 @@
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 4,
|
"execution_count": 8,
|
||||||
"id": "dd6ef6a6",
|
"id": "dd6ef6a6",
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
|
|
@ -133,6 +133,36 @@
|
||||||
"for i in range(len(myLstVar1)): # \"range(n)\" gives you series of numbers from 0 ... n-1\n",
|
"for i in range(len(myLstVar1)): # \"range(n)\" gives you series of numbers from 0 ... n-1\n",
|
||||||
" print(i, myLstVar1[i])"
|
" print(i, myLstVar1[i])"
|
||||||
]
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 13,
|
||||||
|
"id": "52d35884-9507-485e-9637-25d7201ee6ff",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"unsorted myLstVar1 contains 7 items. ['Blue', 'Green', 'Indigo', 'Orange', 'Red', 'Violet', 'Yellow']\n",
|
||||||
|
"sorted myLstVar1 contains 7 items. ['Blue', 'Green', 'Indigo', 'Orange', 'Red', 'Violet', 'Yellow']\n",
|
||||||
|
"0 Blue\n",
|
||||||
|
"1 Green\n",
|
||||||
|
"2 Indigo\n",
|
||||||
|
"3 Orange\n",
|
||||||
|
"4 Red\n",
|
||||||
|
"5 Violet\n",
|
||||||
|
"6 Yellow\n"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"print(\"unsorted myLstVar1 contains \", len(myLstVar1), \" items.\",myLstVar1)\n",
|
||||||
|
"myLstVar1.sort()\n",
|
||||||
|
"print(\"sorted myLstVar1 contains \", len(myLstVar1), \" items.\",myLstVar1)\n",
|
||||||
|
"for i in range(len(myLstVar1)): # \"range(n)\" gives you series of numbers from 0 ... n-1\n",
|
||||||
|
" print(i, myLstVar1[i])"
|
||||||
|
]
|
||||||
}
|
}
|
||||||
],
|
],
|
||||||
"metadata": {
|
"metadata": {
|
||||||
|
|
@ -151,7 +181,7 @@
|
||||||
"name": "python",
|
"name": "python",
|
||||||
"nbconvert_exporter": "python",
|
"nbconvert_exporter": "python",
|
||||||
"pygments_lexer": "ipython3",
|
"pygments_lexer": "ipython3",
|
||||||
"version": "3.11.5"
|
"version": "3.12.7"
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
"nbformat": 4,
|
"nbformat": 4,
|
||||||
|
|
|
||||||
|
|
@ -2,9 +2,13 @@
|
||||||
"cells": [
|
"cells": [
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 2,
|
"execution_count": 1,
|
||||||
"id": "ae280d81",
|
"id": "ae280d81",
|
||||||
"metadata": {},
|
"metadata": {
|
||||||
|
"jupyter": {
|
||||||
|
"source_hidden": true
|
||||||
|
}
|
||||||
|
},
|
||||||
"outputs": [],
|
"outputs": [],
|
||||||
"source": [
|
"source": [
|
||||||
"# CSE-160-D01_2024FA_Tuple-Backgrounder\n",
|
"# CSE-160-D01_2024FA_Tuple-Backgrounder\n",
|
||||||
|
|
@ -30,7 +34,7 @@
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 8,
|
"execution_count": 2,
|
||||||
"id": "987287d1",
|
"id": "987287d1",
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
|
|
@ -48,7 +52,8 @@
|
||||||
"avgDiameterOfEarthInMiles type and length: <class 'tuple'> 1 \n",
|
"avgDiameterOfEarthInMiles type and length: <class 'tuple'> 1 \n",
|
||||||
"\n",
|
"\n",
|
||||||
"lockCombination = ('right24', 'left31', 'right10')\n",
|
"lockCombination = ('right24', 'left31', 'right10')\n",
|
||||||
"lockCombination type and length: <class 'tuple'> 3\n"
|
"lockCombination type and length: <class 'tuple'> 3\n",
|
||||||
|
"\n"
|
||||||
]
|
]
|
||||||
}
|
}
|
||||||
],
|
],
|
||||||
|
|
@ -76,7 +81,7 @@
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 14,
|
"execution_count": 3,
|
||||||
"id": "cc74b5b1",
|
"id": "cc74b5b1",
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
|
|
@ -129,7 +134,7 @@
|
||||||
"name": "python",
|
"name": "python",
|
||||||
"nbconvert_exporter": "python",
|
"nbconvert_exporter": "python",
|
||||||
"pygments_lexer": "ipython3",
|
"pygments_lexer": "ipython3",
|
||||||
"version": "3.11.5"
|
"version": "3.12.7"
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
"nbformat": 4,
|
"nbformat": 4,
|
||||||
|
|
|
||||||
|
|
@ -18,7 +18,7 @@
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 2,
|
"execution_count": 1,
|
||||||
"id": "d20dcd5f",
|
"id": "d20dcd5f",
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
|
|
@ -43,7 +43,7 @@
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 3,
|
"execution_count": 2,
|
||||||
"id": "564c0014",
|
"id": "564c0014",
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
|
|
@ -57,11 +57,11 @@
|
||||||
"| 3.141592653589793|\n",
|
"| 3.141592653589793|\n",
|
||||||
"| 3.141592653589793 |\n",
|
"| 3.141592653589793 |\n",
|
||||||
"\n",
|
"\n",
|
||||||
"Using String variable = 'Python 3.11.5'\n",
|
"Using String variable = 'Python 3.12.7'\n",
|
||||||
"|Python 3.11.5 |\n",
|
"|Python 3.12.7 |\n",
|
||||||
"|Python 3.11.5 |\n",
|
"|Python 3.12.7 |\n",
|
||||||
"| Python 3.11.5|\n",
|
"| Python 3.12.7|\n",
|
||||||
"| Python 3.11.5 |\n"
|
"| Python 3.12.7 |\n"
|
||||||
]
|
]
|
||||||
}
|
}
|
||||||
],
|
],
|
||||||
|
|
@ -92,7 +92,7 @@
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 13,
|
"execution_count": 3,
|
||||||
"id": "9f9b8587",
|
"id": "9f9b8587",
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
|
|
@ -105,10 +105,10 @@
|
||||||
"|========3.141592653589793|\n",
|
"|========3.141592653589793|\n",
|
||||||
"|====3.141592653589793====|\n",
|
"|====3.141592653589793====|\n",
|
||||||
"\n",
|
"\n",
|
||||||
"Using String variable = 'Python 3.11.5'\n",
|
"Using String variable = 'Python 3.12.7'\n",
|
||||||
"|Python 3.11.5============|\n",
|
"|Python 3.12.7============|\n",
|
||||||
"|============Python 3.11.5|\n",
|
"|============Python 3.12.7|\n",
|
||||||
"|======Python 3.11.5======|\n"
|
"|======Python 3.12.7======|\n"
|
||||||
]
|
]
|
||||||
}
|
}
|
||||||
],
|
],
|
||||||
|
|
@ -131,9 +131,11 @@
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 15,
|
"execution_count": 6,
|
||||||
"id": "deee1957",
|
"id": "deee1957",
|
||||||
"metadata": {},
|
"metadata": {
|
||||||
|
"scrolled": true
|
||||||
|
},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
"name": "stdout",
|
"name": "stdout",
|
||||||
|
|
@ -197,9 +199,13 @@
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 16,
|
"execution_count": 5,
|
||||||
"id": "2a3efefd",
|
"id": "2a3efefd",
|
||||||
"metadata": {},
|
"metadata": {
|
||||||
|
"jupyter": {
|
||||||
|
"source_hidden": true
|
||||||
|
}
|
||||||
|
},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
"name": "stdout",
|
"name": "stdout",
|
||||||
|
|
@ -226,7 +232,7 @@
|
||||||
"\n",
|
"\n",
|
||||||
"variable *= -1 \n",
|
"variable *= -1 \n",
|
||||||
"print(f\"Using Numeric {variable = }\") \n",
|
"print(f\"Using Numeric {variable = }\") \n",
|
||||||
"print(f\"With two decimal places and a comma: {variable:,.2f}\") "
|
"print(f\"With two decimal places and a comma: {variable:,.4f}\") "
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
|
|
@ -266,28 +272,10 @@
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 8,
|
"execution_count": null,
|
||||||
"id": "28b43c9c",
|
"id": "28b43c9c",
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [],
|
||||||
{
|
|
||||||
"name": "stdout",
|
|
||||||
"output_type": "stream",
|
|
||||||
"text": [
|
|
||||||
"Number\t\t\tSquare\t\t\tCube\n",
|
|
||||||
" 1\t\t\t 1\t\t\t 1\n",
|
|
||||||
" 2\t\t\t 4\t\t\t 8\n",
|
|
||||||
" 3\t\t\t 9\t\t\t 27\n",
|
|
||||||
" 4\t\t\t 16\t\t\t 64\n",
|
|
||||||
" 5\t\t\t 25\t\t\t 125\n",
|
|
||||||
" 6\t\t\t 36\t\t\t 216\n",
|
|
||||||
" 7\t\t\t 49\t\t\t 343\n",
|
|
||||||
" 8\t\t\t 64\t\t\t 512\n",
|
|
||||||
" 9\t\t\t 81\t\t\t 729\n",
|
|
||||||
"10\t\t\t100\t\t\t1000\n"
|
|
||||||
]
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"source": [
|
"source": [
|
||||||
"# The tab character (\\t) can also be used in an f-string to line up columns, \n",
|
"# The tab character (\\t) can also be used in an f-string to line up columns, \n",
|
||||||
"# particularly when column headings are used: \n",
|
"# particularly when column headings are used: \n",
|
||||||
|
|
@ -298,28 +286,10 @@
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 9,
|
"execution_count": null,
|
||||||
"id": "de6c45f8",
|
"id": "de6c45f8",
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [],
|
||||||
{
|
|
||||||
"name": "stdout",
|
|
||||||
"output_type": "stream",
|
|
||||||
"text": [
|
|
||||||
"Number\t\tSquare\t\tCube\n",
|
|
||||||
" 1.00\t\t 1.00\t\t 1.00\n",
|
|
||||||
" 2.00\t\t 4.00\t\t 8.00\n",
|
|
||||||
" 3.00\t\t 9.00\t\t 27.00\n",
|
|
||||||
" 4.00\t\t 16.00\t\t 64.00\n",
|
|
||||||
" 5.00\t\t 25.00\t\t 125.00\n",
|
|
||||||
" 6.00\t\t 36.00\t\t 216.00\n",
|
|
||||||
" 7.00\t\t 49.00\t\t 343.00\n",
|
|
||||||
" 8.00\t\t 64.00\t\t 512.00\n",
|
|
||||||
" 9.00\t\t 81.00\t\t 729.00\n",
|
|
||||||
"10.00\t\t100.00\t\t 1000.00\n"
|
|
||||||
]
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"source": [
|
"source": [
|
||||||
"# Using either tabs or spacing is acceptable and may depend on which one you are more comfortable with. \n",
|
"# Using either tabs or spacing is acceptable and may depend on which one you are more comfortable with. \n",
|
||||||
"# Either way is acceptable in Python. \n",
|
"# Either way is acceptable in Python. \n",
|
||||||
|
|
@ -333,23 +303,10 @@
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 10,
|
"execution_count": null,
|
||||||
"id": "47fcbb2b",
|
"id": "47fcbb2b",
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [
|
"outputs": [],
|
||||||
{
|
|
||||||
"name": "stdout",
|
|
||||||
"output_type": "stream",
|
|
||||||
"text": [
|
|
||||||
" My Grocery List \n",
|
|
||||||
"==============================\n",
|
|
||||||
"Apples 3\t$ 1.50\n",
|
|
||||||
"Rye Bread 10\t$15.00\n",
|
|
||||||
"Cheese 6\t$13.50\n",
|
|
||||||
" Total:\t$30.00\n"
|
|
||||||
]
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"source": [
|
"source": [
|
||||||
"# This also demonstrates how the use of a value for width will enable the columns to line up. \n",
|
"# This also demonstrates how the use of a value for width will enable the columns to line up. \n",
|
||||||
"# The following program demonstrates the use of strings, decimals, and floats, as well as tabs \n",
|
"# The following program demonstrates the use of strings, decimals, and floats, as well as tabs \n",
|
||||||
|
|
@ -406,7 +363,7 @@
|
||||||
"name": "python",
|
"name": "python",
|
||||||
"nbconvert_exporter": "python",
|
"nbconvert_exporter": "python",
|
||||||
"pygments_lexer": "ipython3",
|
"pygments_lexer": "ipython3",
|
||||||
"version": "3.11.5"
|
"version": "3.12.7"
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
"nbformat": 4,
|
"nbformat": 4,
|
||||||
|
|
|
||||||
Binary file not shown.
|
After Width: | Height: | Size: 46 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 60 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 55 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 61 KiB |
|
|
@ -0,0 +1,21 @@
|
||||||
|
|
||||||
|
from pprint import pprint
|
||||||
|
|
||||||
|
addressList = ["John Smith", "1 Main St", "Anycity", "Ma", "01102"]
|
||||||
|
|
||||||
|
print(addressList)
|
||||||
|
|
||||||
|
print(sorted(addressList))
|
||||||
|
|
||||||
|
addressDictionary = {'Name':"John Smith", 'Address':"1 Main St", 'City': "Anycity",
|
||||||
|
'State':"Ma", 'ZipCode': "01102"}
|
||||||
|
|
||||||
|
print(addressDictionary)
|
||||||
|
|
||||||
|
print(addressDictionary.keys())
|
||||||
|
print(addressDictionary.values())
|
||||||
|
|
||||||
|
for Item in addressDictionary.keys():
|
||||||
|
print(f"{Item:10s} {addressDictionary[Item]}")
|
||||||
|
|
||||||
|
pprint(addressDictionary)
|
||||||
|
|
@ -0,0 +1,170 @@
|
||||||
|
Duration,Pulse,Maxpulse,Calories
|
||||||
|
60,110,130,409.1
|
||||||
|
60,117,145,479.0
|
||||||
|
60,103,135,340.0
|
||||||
|
45,109,175,282.4
|
||||||
|
45,117,148,406.0
|
||||||
|
60,102,127,300.5
|
||||||
|
60,110,136,374.0
|
||||||
|
45,104,134,253.3
|
||||||
|
30,109,133,195.1
|
||||||
|
60,98,124,269.0
|
||||||
|
60,103,147,329.3
|
||||||
|
60,100,120,250.7
|
||||||
|
60,106,128,345.3
|
||||||
|
60,104,132,379.3
|
||||||
|
60,98,123,275.0
|
||||||
|
60,98,120,215.2
|
||||||
|
60,100,120,300.0
|
||||||
|
45,90,112,
|
||||||
|
60,103,123,323.0
|
||||||
|
45,97,125,243.0
|
||||||
|
60,108,131,364.2
|
||||||
|
45,100,119,282.0
|
||||||
|
60,130,101,300.0
|
||||||
|
45,105,132,246.0
|
||||||
|
60,102,126,334.5
|
||||||
|
60,100,120,250.0
|
||||||
|
60,92,118,241.0
|
||||||
|
60,103,132
|
||||||
|
60,100,132,280.0
|
||||||
|
60,102,129,380.3
|
||||||
|
60,92,115,243.0
|
||||||
|
45,90,112,180.1
|
||||||
|
60,101,124,299.0
|
||||||
|
60,93,113,223.0
|
||||||
|
60,107,136,361.0
|
||||||
|
60,114,140,415.0
|
||||||
|
60,102,127,300.5
|
||||||
|
60,100,120,300.1
|
||||||
|
60,100,120,300.0
|
||||||
|
45,104,129,266.0
|
||||||
|
45,90,112,180.1
|
||||||
|
60,98,126,286.0
|
||||||
|
60,100,122,329.4
|
||||||
|
60,111,138,400.0
|
||||||
|
60,111,131,397.0
|
||||||
|
60,99,119,273.0
|
||||||
|
60,109,153,387.6
|
||||||
|
45,111,136,300.0
|
||||||
|
45,108,129,298.0
|
||||||
|
60,111,139,397.6
|
||||||
|
60,107,136,380.2
|
||||||
|
80,123,146,643.1
|
||||||
|
60,106,130,263.0
|
||||||
|
60,118,151,486.0
|
||||||
|
30,136,175,238.0
|
||||||
|
60,121,146,450.7
|
||||||
|
60,118,121,413.0
|
||||||
|
45,115,144,305.0
|
||||||
|
20,153,172,226.4
|
||||||
|
45,123,152,321.0
|
||||||
|
210,108,160,1376.0
|
||||||
|
160,110,137,1034.4
|
||||||
|
160,109,135,853.0
|
||||||
|
45,118,141,341.0
|
||||||
|
20,110,130,131.4
|
||||||
|
180,90,130,800.4
|
||||||
|
150,105,135,873.4
|
||||||
|
150,107,130,816.0
|
||||||
|
20,106,136,110.4
|
||||||
|
300,108,143,1500.2
|
||||||
|
150,97,129,1115.0
|
||||||
|
60,109,153,387.6
|
||||||
|
90,100,127,700.0
|
||||||
|
150,97,127,953.2
|
||||||
|
45,114,146,304.0
|
||||||
|
90,98,125,563.2
|
||||||
|
45,105,134,251.0
|
||||||
|
45,110,141,300.0
|
||||||
|
120,100,130,500.4
|
||||||
|
270,100,131,1729.0
|
||||||
|
30,159,182,319.2
|
||||||
|
45,149,169,344.0
|
||||||
|
30,103,139,151.1
|
||||||
|
120,100,130,500.0
|
||||||
|
45,100,120,225.3
|
||||||
|
30,151,170,300.1
|
||||||
|
45,102,136,234.0
|
||||||
|
120,100,157,1000.1
|
||||||
|
45,129,103,242.0
|
||||||
|
20,83,107,50.3
|
||||||
|
180,101,127,600.1
|
||||||
|
45,107,137,
|
||||||
|
30,90,107,105.3
|
||||||
|
15,80,100,50.5
|
||||||
|
20,150,171,127.4
|
||||||
|
20,151,168,229.4
|
||||||
|
30,95,128,128.2
|
||||||
|
25,152,168,244.2
|
||||||
|
30,109,131,188.2
|
||||||
|
90,93,124,604.1
|
||||||
|
20,95,112,77.7
|
||||||
|
90,90,110,500.0
|
||||||
|
90,90,100,500.0
|
||||||
|
90,90,100,500.4
|
||||||
|
30,92,108,92.7
|
||||||
|
30,93,128,124.0
|
||||||
|
180,90,120,800.3
|
||||||
|
30,90,120,86.2
|
||||||
|
90,90,120,500.3
|
||||||
|
210,137,184,1860.4
|
||||||
|
60,102,124,325.2
|
||||||
|
45,107,124,275.0
|
||||||
|
15,124,139,124.2
|
||||||
|
45,100,120,225.3
|
||||||
|
60,108,131,367.6
|
||||||
|
60,108,151,351.7
|
||||||
|
60,116,141,443.0
|
||||||
|
60,97,122,277.4
|
||||||
|
60,105,125,
|
||||||
|
60,103,124,332.7
|
||||||
|
30,112,137,193.9
|
||||||
|
45,100,120,100.7
|
||||||
|
60,119,169,336.7
|
||||||
|
60,107,127,344.9
|
||||||
|
60,111,151,368.5
|
||||||
|
60,98,122,271.0
|
||||||
|
60,97,124,275.3
|
||||||
|
60,109,127,382.0
|
||||||
|
90,99,125,466.4
|
||||||
|
60,114,151,384.0
|
||||||
|
60,104,134,342.5
|
||||||
|
60,107,138,357.5
|
||||||
|
60,103,133,335.0
|
||||||
|
60,106,132,327.5
|
||||||
|
60,103,136,339.0
|
||||||
|
20,136,156,189.0
|
||||||
|
45,117,143,317.7
|
||||||
|
45,115,137,318.0
|
||||||
|
45,113,138,308.0
|
||||||
|
20,141,162,222.4
|
||||||
|
60,108,135,390.0
|
||||||
|
60,97,127,
|
||||||
|
45,100,120,250.4
|
||||||
|
45,122,149,335.4
|
||||||
|
60,136,170,470.2
|
||||||
|
45,106,126,270.8
|
||||||
|
60,107,136,400.0
|
||||||
|
60,112,146,361.9
|
||||||
|
30,103,127,185.0
|
||||||
|
60,110,150,409.4
|
||||||
|
60,106,134,343.0
|
||||||
|
60,109,129,353.2
|
||||||
|
60,109,138,374.0
|
||||||
|
30,150,167,275.8
|
||||||
|
60,105,128,328.0
|
||||||
|
60,111,151,368.5
|
||||||
|
60,97,131,270.4
|
||||||
|
60,100,120,270.4
|
||||||
|
60,114,150,382.8
|
||||||
|
30,80,120,240.9
|
||||||
|
30,85,120,250.4
|
||||||
|
45,90,130,260.4
|
||||||
|
45,95,130,270.0
|
||||||
|
45,100,140,280.9
|
||||||
|
60,105,140,290.8
|
||||||
|
60,110,145,300.4
|
||||||
|
60,115,145,310.2
|
||||||
|
75,120,150,320.4
|
||||||
|
75,125,150,330.4
|
||||||
|
Can't render this file because it has a wrong number of fields in line 29.
|
|
|
@ -0,0 +1,8 @@
|
||||||
|
DogName,BirthYear,Breed,Color
|
||||||
|
Harry,2007,Chinook,Buff
|
||||||
|
Shenanigans,2008,Chinook,Tawney
|
||||||
|
Mandy,2016,Chinook,Tawney
|
||||||
|
Tanner,2002,Golden Retriever,Tan
|
||||||
|
Rusty,2004,Golden Retriever,Tan
|
||||||
|
Gimli,2022,Chinook,Tawney
|
||||||
|
Yukon Jack,2020,Chinook,Tawney
|
||||||
|
|
|
@ -0,0 +1,7 @@
|
||||||
|
# https://www.w3schools.com/python/pandas/pandas_csv.asp
|
||||||
|
|
||||||
|
import pandas as pd
|
||||||
|
|
||||||
|
df = pd.read_csv('data.csv')
|
||||||
|
|
||||||
|
print(df.to_string())
|
||||||
|
|
@ -0,0 +1,7 @@
|
||||||
|
# https://www.w3schools.com/python/pandas/pandas_csv.asp
|
||||||
|
|
||||||
|
import pandas as pd
|
||||||
|
|
||||||
|
df = pd.read_csv('dogs.csv')
|
||||||
|
|
||||||
|
print(df.to_string())
|
||||||
|
|
@ -0,0 +1,9 @@
|
||||||
|
# https://www.w3schools.com/python/pandas/pandas_csv.asp
|
||||||
|
|
||||||
|
import pandas as pd
|
||||||
|
|
||||||
|
df = pd.read_csv('data.csv')
|
||||||
|
|
||||||
|
print(df.head())
|
||||||
|
|
||||||
|
print(df.tail())
|
||||||
|
|
@ -0,0 +1,35 @@
|
||||||
|
|
||||||
|
line = "7/5/2016,123,638.5"
|
||||||
|
|
||||||
|
# split line on commas
|
||||||
|
lineFields = line.split(',')
|
||||||
|
|
||||||
|
print(lineFields)
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
# Individual columns from the spreadsheet
|
||||||
|
print(lineFields[0], type(lineFields[0]) )
|
||||||
|
print(lineFields[1], type(lineFields[1]) )
|
||||||
|
print(lineFields[2], type(lineFields[2]) )
|
||||||
|
|
||||||
|
# Convert ISO date --> 20161115 or 2016-1115 or 2016-11-15
|
||||||
|
|
||||||
|
|
||||||
|
dateFields = lineFields[0].split('/')
|
||||||
|
print(dateFields)
|
||||||
|
|
||||||
|
#print(len(dateFields[0]))
|
||||||
|
#print(len(dateFields[1]))
|
||||||
|
|
||||||
|
if(len(dateFields[0]) == 1):
|
||||||
|
dateFields[0] = "0"+ dateFields[0]
|
||||||
|
|
||||||
|
if(len(dateFields[1]) == 1):
|
||||||
|
dateFields[1] = "0"+ dateFields[1]
|
||||||
|
|
||||||
|
print(dateFields)
|
||||||
|
|
||||||
|
isoDate = dateFields[2] + dateFields[0] + dateFields[1]
|
||||||
|
|
||||||
|
print("ISO Date = ", isoDate)
|
||||||
|
|
@ -0,0 +1,11 @@
|
||||||
|
# Read a csv file from the current directory
|
||||||
|
# import the csv function library
|
||||||
|
import csv
|
||||||
|
|
||||||
|
filename = "dogs.csv"
|
||||||
|
|
||||||
|
with open(filename,'r') as csvfile:
|
||||||
|
csvData = csv.reader(csvfile,delimiter = ',',quotechar = '"')
|
||||||
|
for row in csvData:
|
||||||
|
print(row)
|
||||||
|
|
||||||
|
|
@ -0,0 +1,17 @@
|
||||||
|
|
||||||
|
dataHeaders = "id,value,feed_id,created_at,lat,lon,ele"
|
||||||
|
|
||||||
|
dataValues = "0FV1TKJ51XRHX03W57F3PVC7K8,77.2,2756158,2025-03-17 18:16:42 UTC,,,"
|
||||||
|
|
||||||
|
print(dataHeaders)
|
||||||
|
|
||||||
|
headerFields = dataHeaders.split(",")
|
||||||
|
print(headerFields)
|
||||||
|
|
||||||
|
print(dataValues)
|
||||||
|
valuesFields = dataValues.split(",")
|
||||||
|
print(valuesFields)
|
||||||
|
|
||||||
|
myFields = [valuesFields[3],valuesFields[1]]
|
||||||
|
|
||||||
|
print(myFields)
|
||||||
|
|
@ -0,0 +1,170 @@
|
||||||
|
Duration,Pulse,Maxpulse,Calories
|
||||||
|
60,110,130,409.1
|
||||||
|
60,117,145,479.0
|
||||||
|
60,103,135,340.0
|
||||||
|
45,109,175,282.4
|
||||||
|
45,117,148,406.0
|
||||||
|
60,102,127,300.5
|
||||||
|
60,110,136,374.0
|
||||||
|
45,104,134,253.3
|
||||||
|
30,109,133,195.1
|
||||||
|
60,98,124,269.0
|
||||||
|
60,103,147,329.3
|
||||||
|
60,100,120,250.7
|
||||||
|
60,106,128,345.3
|
||||||
|
60,104,132,379.3
|
||||||
|
60,98,123,275.0
|
||||||
|
60,98,120,215.2
|
||||||
|
60,100,120,300.0
|
||||||
|
45,90,112,
|
||||||
|
60,103,123,323.0
|
||||||
|
45,97,125,243.0
|
||||||
|
60,108,131,364.2
|
||||||
|
45,100,119,282.0
|
||||||
|
60,130,101,300.0
|
||||||
|
45,105,132,246.0
|
||||||
|
60,102,126,334.5
|
||||||
|
60,100,120,250.0
|
||||||
|
60,92,118,241.0
|
||||||
|
60,103,132
|
||||||
|
60,100,132,280.0
|
||||||
|
60,102,129,380.3
|
||||||
|
60,92,115,243.0
|
||||||
|
45,90,112,180.1
|
||||||
|
60,101,124,299.0
|
||||||
|
60,93,113,223.0
|
||||||
|
60,107,136,361.0
|
||||||
|
60,114,140,415.0
|
||||||
|
60,102,127,300.5
|
||||||
|
60,100,120,300.1
|
||||||
|
60,100,120,300.0
|
||||||
|
45,104,129,266.0
|
||||||
|
45,90,112,180.1
|
||||||
|
60,98,126,286.0
|
||||||
|
60,100,122,329.4
|
||||||
|
60,111,138,400.0
|
||||||
|
60,111,131,397.0
|
||||||
|
60,99,119,273.0
|
||||||
|
60,109,153,387.6
|
||||||
|
45,111,136,300.0
|
||||||
|
45,108,129,298.0
|
||||||
|
60,111,139,397.6
|
||||||
|
60,107,136,380.2
|
||||||
|
80,123,146,643.1
|
||||||
|
60,106,130,263.0
|
||||||
|
60,118,151,486.0
|
||||||
|
30,136,175,238.0
|
||||||
|
60,121,146,450.7
|
||||||
|
60,118,121,413.0
|
||||||
|
45,115,144,305.0
|
||||||
|
20,153,172,226.4
|
||||||
|
45,123,152,321.0
|
||||||
|
210,108,160,1376.0
|
||||||
|
160,110,137,1034.4
|
||||||
|
160,109,135,853.0
|
||||||
|
45,118,141,341.0
|
||||||
|
20,110,130,131.4
|
||||||
|
180,90,130,800.4
|
||||||
|
150,105,135,873.4
|
||||||
|
150,107,130,816.0
|
||||||
|
20,106,136,110.4
|
||||||
|
300,108,143,1500.2
|
||||||
|
150,97,129,1115.0
|
||||||
|
60,109,153,387.6
|
||||||
|
90,100,127,700.0
|
||||||
|
150,97,127,953.2
|
||||||
|
45,114,146,304.0
|
||||||
|
90,98,125,563.2
|
||||||
|
45,105,134,251.0
|
||||||
|
45,110,141,300.0
|
||||||
|
120,100,130,500.4
|
||||||
|
270,100,131,1729.0
|
||||||
|
30,159,182,319.2
|
||||||
|
45,149,169,344.0
|
||||||
|
30,103,139,151.1
|
||||||
|
120,100,130,500.0
|
||||||
|
45,100,120,225.3
|
||||||
|
30,151,170,300.1
|
||||||
|
45,102,136,234.0
|
||||||
|
120,100,157,1000.1
|
||||||
|
45,129,103,242.0
|
||||||
|
20,83,107,50.3
|
||||||
|
180,101,127,600.1
|
||||||
|
45,107,137,
|
||||||
|
30,90,107,105.3
|
||||||
|
15,80,100,50.5
|
||||||
|
20,150,171,127.4
|
||||||
|
20,151,168,229.4
|
||||||
|
30,95,128,128.2
|
||||||
|
25,152,168,244.2
|
||||||
|
30,109,131,188.2
|
||||||
|
90,93,124,604.1
|
||||||
|
20,95,112,77.7
|
||||||
|
90,90,110,500.0
|
||||||
|
90,90,100,500.0
|
||||||
|
90,90,100,500.4
|
||||||
|
30,92,108,92.7
|
||||||
|
30,93,128,124.0
|
||||||
|
180,90,120,800.3
|
||||||
|
30,90,120,86.2
|
||||||
|
90,90,120,500.3
|
||||||
|
210,137,184,1860.4
|
||||||
|
60,102,124,325.2
|
||||||
|
45,107,124,275.0
|
||||||
|
15,124,139,124.2
|
||||||
|
45,100,120,225.3
|
||||||
|
60,108,131,367.6
|
||||||
|
60,108,151,351.7
|
||||||
|
60,116,141,443.0
|
||||||
|
60,97,122,277.4
|
||||||
|
60,105,125,
|
||||||
|
60,103,124,332.7
|
||||||
|
30,112,137,193.9
|
||||||
|
45,100,120,100.7
|
||||||
|
60,119,169,336.7
|
||||||
|
60,107,127,344.9
|
||||||
|
60,111,151,368.5
|
||||||
|
60,98,122,271.0
|
||||||
|
60,97,124,275.3
|
||||||
|
60,109,127,382.0
|
||||||
|
90,99,125,466.4
|
||||||
|
60,114,151,384.0
|
||||||
|
60,104,134,342.5
|
||||||
|
60,107,138,357.5
|
||||||
|
60,103,133,335.0
|
||||||
|
60,106,132,327.5
|
||||||
|
60,103,136,339.0
|
||||||
|
20,136,156,189.0
|
||||||
|
45,117,143,317.7
|
||||||
|
45,115,137,318.0
|
||||||
|
45,113,138,308.0
|
||||||
|
20,141,162,222.4
|
||||||
|
60,108,135,390.0
|
||||||
|
60,97,127,
|
||||||
|
45,100,120,250.4
|
||||||
|
45,122,149,335.4
|
||||||
|
60,136,170,470.2
|
||||||
|
45,106,126,270.8
|
||||||
|
60,107,136,400.0
|
||||||
|
60,112,146,361.9
|
||||||
|
30,103,127,185.0
|
||||||
|
60,110,150,409.4
|
||||||
|
60,106,134,343.0
|
||||||
|
60,109,129,353.2
|
||||||
|
60,109,138,374.0
|
||||||
|
30,150,167,275.8
|
||||||
|
60,105,128,328.0
|
||||||
|
60,111,151,368.5
|
||||||
|
60,97,131,270.4
|
||||||
|
60,100,120,270.4
|
||||||
|
60,114,150,382.8
|
||||||
|
30,80,120,240.9
|
||||||
|
30,85,120,250.4
|
||||||
|
45,90,130,260.4
|
||||||
|
45,95,130,270.0
|
||||||
|
45,100,140,280.9
|
||||||
|
60,105,140,290.8
|
||||||
|
60,110,145,300.4
|
||||||
|
60,115,145,310.2
|
||||||
|
75,120,150,320.4
|
||||||
|
75,125,150,330.4
|
||||||
|
Can't render this file because it has a wrong number of fields in line 29.
|
|
|
@ -0,0 +1,3 @@
|
||||||
|
Hello! Welcome to demofile.txt
|
||||||
|
This file is for testing purposes.
|
||||||
|
Good Luck!
|
||||||
|
|
@ -0,0 +1,8 @@
|
||||||
|
DogName,BirthYear,Breed,Color
|
||||||
|
Harry,2007,Chinook,Buff
|
||||||
|
Shenanigans,2008,Chinook,Tawney
|
||||||
|
Mandy,2016,Chinook,Tawney
|
||||||
|
Tanner,2002,Golden Retriever,Tan
|
||||||
|
Rusty,2004,Golden Retriever,Tan
|
||||||
|
Gimli,2022,Chinook,Tawney
|
||||||
|
Yukon Jack,2020,Chinook,Tawney
|
||||||
|
|
|
@ -0,0 +1,8 @@
|
||||||
|
DogName,BirthYear,Breed,Color
|
||||||
|
Harry,2007,Chinook,Buff
|
||||||
|
Shenanigans,2008,Chinook,Tawney
|
||||||
|
Mandy,2016,Chinook,Tawney
|
||||||
|
Tanner,2002,Golden Retriever,Tan
|
||||||
|
Rusty,2004,Golden Retriever,Tan
|
||||||
|
Gimli,2022,Chinook,Tawney
|
||||||
|
Yukon Jack,2020,Chinook,Tawney
|
||||||
|
|
|
@ -0,0 +1,5 @@
|
||||||
|
# https://www.w3schools.com/python/python_file_open.asp
|
||||||
|
|
||||||
|
f = open("demofile.txt", "r")
|
||||||
|
|
||||||
|
print(f.read())
|
||||||
|
|
@ -0,0 +1,9 @@
|
||||||
|
# https://www.w3schools.com/python/python_file_write.asp
|
||||||
|
|
||||||
|
f = open("demofile2.txt", "a")
|
||||||
|
f.write("Now the file has more content!")
|
||||||
|
f.close()
|
||||||
|
|
||||||
|
#open and read the file after the appending:
|
||||||
|
f = open("demofile2.txt", "r")
|
||||||
|
print(f.read())
|
||||||
|
|
@ -0,0 +1,10 @@
|
||||||
|
# https://www.w3schools.com/python/python_file_write.asp
|
||||||
|
|
||||||
|
f = open("demofile3.txt", "w")
|
||||||
|
f.write("Woops! I have deleted the content!")
|
||||||
|
f.close()
|
||||||
|
|
||||||
|
#open and read the file after the overwriting:
|
||||||
|
f = open("demofile3.txt", "r")
|
||||||
|
print(f.read())
|
||||||
|
|
||||||
|
|
@ -0,0 +1,39 @@
|
||||||
|
|
||||||
|
This is from file dogs-with-hidden-char.csv
|
||||||
|
|
||||||
|
Sometimes hidden characters are exported from the spreadsheet program. Run csvline2.py
|
||||||
|
with the filename set to dogs-with-hidden-char.csv
|
||||||
|
|
||||||
|
(base) edbigos@Edwards-MacBook-Pro-4 csvlines % od -bc dogs-with-hidden-char.csv
|
||||||
|
0000000 357 273 277 104 157 147 116 141 155 145 054 102 151 162 164 150
|
||||||
|
357 273 277 D o g N a m e , B i r t h
|
||||||
|
0000020 131 145 141 162 054 102 162 145 145 144 054 103 157 154 157 162
|
||||||
|
Y e a r , B r e e d , C o l o r
|
||||||
|
0000040 015 012 110 141 162 162 171 054 062 060 060 067 054 103 150 151
|
||||||
|
\r \n H a r r y , 2 0 0 7 , C h i
|
||||||
|
0000060 156 157 157 153 054 102 165 146 146 015 012 123 150 145 156 141
|
||||||
|
n o o k , B u f f \r \n S h e n a
|
||||||
|
0000100 156 151 147 141 156 163 054 062 060 060 070 054 103 150 151 156
|
||||||
|
n i g a n s , 2 0 0 8 , C h i n
|
||||||
|
0000120 157 157 153 054 124 141 167 156 145 171 015 012 115 141 156 144
|
||||||
|
o o k , T a w n e y \r \n M a n d
|
||||||
|
0000140 171 054 062 060 061 066 054 103 150 151 156 157 157 153 054 124
|
||||||
|
y , 2 0 1 6 , C h i n o o k , T
|
||||||
|
0000160 141 167 156 145 171 015 012 124 141 156 156 145 162 054 062 060
|
||||||
|
a w n e y \r \n T a n n e r , 2 0
|
||||||
|
0000200 060 062 054 107 157 154 144 145 156 040 122 145 164 162 151 145
|
||||||
|
0 2 , G o l d e n R e t r i e
|
||||||
|
0000220 166 145 162 054 124 141 156 015 012 122 165 163 164 171 054 062
|
||||||
|
v e r , T a n \r \n R u s t y , 2
|
||||||
|
0000240 060 060 064 054 107 157 154 144 145 156 040 122 145 164 162 151
|
||||||
|
0 0 4 , G o l d e n R e t r i
|
||||||
|
0000260 145 166 145 162 054 124 141 156 015 012 107 151 155 154 151 054
|
||||||
|
e v e r , T a n \r \n G i m l i ,
|
||||||
|
0000300 062 060 062 062 054 103 150 151 156 157 157 153 054 124 141 167
|
||||||
|
2 0 2 2 , C h i n o o k , T a w
|
||||||
|
0000320 156 145 171 015 012 131 165 153 157 156 040 112 141 143 153 054
|
||||||
|
n e y \r \n Y u k o n J a c k ,
|
||||||
|
0000340 062 060 062 060 054 103 150 151 156 157 157 153 054 124 141 167
|
||||||
|
2 0 2 0 , C h i n o o k , T a w
|
||||||
|
0000360 156 145 171
|
||||||
|
n e y
|
||||||
|
|
@ -0,0 +1,7 @@
|
||||||
|
# https://www.w3schools.com/python/python_file_remove.asp
|
||||||
|
|
||||||
|
import os
|
||||||
|
if os.path.exists("demofile3.txt"):
|
||||||
|
os.remove("demofile3.txt")
|
||||||
|
else:
|
||||||
|
print("The file does not exist")
|
||||||
|
|
@ -0,0 +1,6 @@
|
||||||
|
Date,Quan,Cost,Total
|
||||||
|
4/8/25,1,$1.00,$1.00
|
||||||
|
4/8/25,2,$0.97,$1.94
|
||||||
|
4/8/25,4,$45.00,$180.00
|
||||||
|
4/8/25,6,$12.00,$72.00
|
||||||
|
4/8/25,9,$11.00,$99.00
|
||||||
|
Binary file not shown.
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,7 @@
|
||||||
|
The columns in the census data correspond to:
|
||||||
|
|
||||||
|
Column Data
|
||||||
|
1 A "Name"
|
||||||
|
2 Frequency in percent
|
||||||
|
3 Cumulative Frequency in percent
|
||||||
|
4 Rank
|
||||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,29 @@
|
||||||
|
#!/usr/bin/python3
|
||||||
|
|
||||||
|
## ============================ One time initializations ========================
|
||||||
|
#fileName = "testdata.txt" # this generates an error
|
||||||
|
fileName = "female-first.txt"
|
||||||
|
|
||||||
|
|
||||||
|
## ============================ Open and process file(s) ========================
|
||||||
|
|
||||||
|
try:
|
||||||
|
inFile = open(fileName,'r')
|
||||||
|
|
||||||
|
count = 1
|
||||||
|
runFlag = True
|
||||||
|
while(runFlag): # Process while true
|
||||||
|
# print(count,line.rstrip("\n"))
|
||||||
|
line = inFile.readline()
|
||||||
|
if line == "":
|
||||||
|
runFlag == False
|
||||||
|
else:
|
||||||
|
line = line.rstrip("\n")
|
||||||
|
print(count,line)
|
||||||
|
count = count + 1
|
||||||
|
|
||||||
|
except:
|
||||||
|
print("Some error occurred. Ending here")
|
||||||
|
exit(-1)
|
||||||
|
|
||||||
|
inFile.close()
|
||||||
|
|
@ -0,0 +1,28 @@
|
||||||
|
#!/usr/bin/python3
|
||||||
|
|
||||||
|
## ============================ One time initializations ========================
|
||||||
|
fileName = "female-first.txt"
|
||||||
|
|
||||||
|
|
||||||
|
## ============================ Open and process file(s) ========================
|
||||||
|
|
||||||
|
try:
|
||||||
|
inFile = open(fileName,'r')
|
||||||
|
|
||||||
|
count = 1
|
||||||
|
runFlag = True
|
||||||
|
while(runFlag): # Process while true
|
||||||
|
# print(count,line.rstrip("\n"))
|
||||||
|
line = inFile.readline()
|
||||||
|
if not (line == ""):
|
||||||
|
line = line.rstrip("\n")
|
||||||
|
print(count,line)
|
||||||
|
count = count + 1
|
||||||
|
else:
|
||||||
|
runFlag == False
|
||||||
|
|
||||||
|
except:
|
||||||
|
print("Some error occurred. Ending here")
|
||||||
|
exit(-1)
|
||||||
|
|
||||||
|
inFile.close()
|
||||||
|
|
@ -0,0 +1,28 @@
|
||||||
|
#!/usr/bin/python3
|
||||||
|
|
||||||
|
## ============================ One time initializations ========================
|
||||||
|
fileName = "testdata.txt"
|
||||||
|
|
||||||
|
|
||||||
|
## ============================ Open and process file(s) ========================
|
||||||
|
|
||||||
|
try:
|
||||||
|
inFile = open(fileName,'r')
|
||||||
|
|
||||||
|
count = 1
|
||||||
|
runFlag = True
|
||||||
|
while(1): # Process while true
|
||||||
|
|
||||||
|
line = inFile.readline()
|
||||||
|
if line == "": # Exit on empty line == end of file
|
||||||
|
break
|
||||||
|
|
||||||
|
line = line.rstrip("\n")
|
||||||
|
print(count,line)
|
||||||
|
count = count + 1
|
||||||
|
|
||||||
|
except:
|
||||||
|
print("Some error occurred. Ending here")
|
||||||
|
exit(-1)
|
||||||
|
|
||||||
|
inFile.close()
|
||||||
|
|
@ -0,0 +1,35 @@
|
||||||
|
#!/usr/bin/python3
|
||||||
|
import re
|
||||||
|
|
||||||
|
## ============================ One time initializations ========================
|
||||||
|
fileName = "female-first.txt"
|
||||||
|
outFileName = "female-first.csv"
|
||||||
|
|
||||||
|
|
||||||
|
## ============================ Open and process file(s) ========================
|
||||||
|
|
||||||
|
try:
|
||||||
|
inFile = open(fileName,'r')
|
||||||
|
outFile = open(outFileName,'w')
|
||||||
|
|
||||||
|
count = 1
|
||||||
|
runFlag = True
|
||||||
|
while(1): # Process while true
|
||||||
|
|
||||||
|
line = inFile.readline()
|
||||||
|
if line == "": # Exit on empty line == end of file
|
||||||
|
break
|
||||||
|
|
||||||
|
line = line.rstrip("\n")
|
||||||
|
line = line.lstrip().rstrip()
|
||||||
|
print(count,line)
|
||||||
|
csvLine = re.sub(' +',',',line)
|
||||||
|
print("\t",csvLine)
|
||||||
|
outFile.write(csvLine + "\n")
|
||||||
|
count = count + 1
|
||||||
|
|
||||||
|
except:
|
||||||
|
print("Some error occurred. Ending here")
|
||||||
|
exit(-1)
|
||||||
|
|
||||||
|
inFile.close()
|
||||||
|
|
@ -0,0 +1,25 @@
|
||||||
|
#!/usr/bin/python3
|
||||||
|
|
||||||
|
# See https://stackabuse.com/read-a-file-line-by-line-in-python/
|
||||||
|
# for more information
|
||||||
|
# Just try reading it line by line on the first attempt.
|
||||||
|
|
||||||
|
fileName = "testdata.txt"
|
||||||
|
try:
|
||||||
|
inFile = open(fileName,'r')
|
||||||
|
|
||||||
|
count = 1
|
||||||
|
line = inFile.readline()
|
||||||
|
line = line.rstrip("\n")
|
||||||
|
while(line): # Read line and place in variable named line
|
||||||
|
# print(count,line.rstrip("\n"))
|
||||||
|
print(count,line)
|
||||||
|
line = inFile.readline()
|
||||||
|
line = line.rstrip("\n")
|
||||||
|
count = count + 1
|
||||||
|
|
||||||
|
except:
|
||||||
|
print("Some error occurred. Ending here")
|
||||||
|
exit(-1)
|
||||||
|
|
||||||
|
inFile.close()
|
||||||
|
|
@ -0,0 +1,38 @@
|
||||||
|
#!/usr/bin/python3
|
||||||
|
|
||||||
|
## ============================ One time initializations ========================
|
||||||
|
fileName = "female-first.txt"
|
||||||
|
|
||||||
|
nameToSearch = input("Enter a first name: ")
|
||||||
|
nameToSearch = nameToSearch.upper()
|
||||||
|
|
||||||
|
## ============================ Open and process file(s) ========================
|
||||||
|
|
||||||
|
try:
|
||||||
|
inFile = open(fileName,'r')
|
||||||
|
|
||||||
|
count = 1
|
||||||
|
runFlag = True
|
||||||
|
while(1): # Process while true
|
||||||
|
|
||||||
|
line = inFile.readline()
|
||||||
|
if line == "": # Exit on empty line == end of file
|
||||||
|
break
|
||||||
|
|
||||||
|
line = line.rstrip("\n")
|
||||||
|
# print(count,line)
|
||||||
|
fieldList = line.split(" ")
|
||||||
|
# print(fieldList)
|
||||||
|
print(fieldList[0],len(fieldList[0]))
|
||||||
|
|
||||||
|
if nameToSearch == fieldList[0] :
|
||||||
|
print("Matched {} = {} at position {}".format(nameToSearch,fieldList[0],count))
|
||||||
|
break
|
||||||
|
|
||||||
|
count = count + 1
|
||||||
|
|
||||||
|
except:
|
||||||
|
print("Some error occurred. Ending here")
|
||||||
|
exit(-1)
|
||||||
|
|
||||||
|
inFile.close()
|
||||||
|
|
@ -0,0 +1,34 @@
|
||||||
|
#!/usr/bin/python3
|
||||||
|
|
||||||
|
## ============================ One time initializations ========================
|
||||||
|
fileName = "female-first.txt"
|
||||||
|
|
||||||
|
|
||||||
|
## ============================ Open and process file(s) ========================
|
||||||
|
|
||||||
|
try:
|
||||||
|
inFile = open(fileName,'r')
|
||||||
|
|
||||||
|
count = 1
|
||||||
|
runFlag = True
|
||||||
|
while(1): # Process while true
|
||||||
|
|
||||||
|
line = inFile.readline()
|
||||||
|
if line == "": # Exit on empty line == end of file
|
||||||
|
break
|
||||||
|
|
||||||
|
line = line.rstrip("\n")
|
||||||
|
print(count,line)
|
||||||
|
line = line.replace(" "," ")
|
||||||
|
print("\t",count,line)
|
||||||
|
fieldList = line.split(" ")
|
||||||
|
print(fieldList)
|
||||||
|
for field in fieldList:
|
||||||
|
print(field)
|
||||||
|
count = count + 1
|
||||||
|
|
||||||
|
except:
|
||||||
|
print("Some error occurred. Ending here")
|
||||||
|
exit(-1)
|
||||||
|
|
||||||
|
inFile.close()
|
||||||
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,8 @@
|
||||||
|
DogName,BirthYear,Breed,Color
|
||||||
|
Harry,2007,Chinook,Buff
|
||||||
|
Shenanigans,2008,Chinook,Tawney
|
||||||
|
Mandy,2016,Chinook,Tawney
|
||||||
|
Tanner,2002,Golden Retriever,Tan
|
||||||
|
Rusty,2004,Golden Retriever,Tan
|
||||||
|
Gimli,2022,Chinook,Tawney
|
||||||
|
Yukon Jack,2020,Chinook,Tawney
|
||||||
|
Binary file not shown.
|
|
@ -0,0 +1,23 @@
|
||||||
|
#!/usr/bin/python3
|
||||||
|
import sys
|
||||||
|
|
||||||
|
# See https://stackabuse.com/read-a-file-line-by-line-in-python/
|
||||||
|
# for more information
|
||||||
|
# Just try reading it line by line on the first attempt.
|
||||||
|
filename = "testxdata.txt"
|
||||||
|
try:
|
||||||
|
inFile = open(filename,'r')
|
||||||
|
|
||||||
|
count = 1
|
||||||
|
line = inFile.readline()
|
||||||
|
line = line.rstrip("\n")
|
||||||
|
while(line): # Read line and place in variable named line
|
||||||
|
# print(count,line.rstrip("\n"))
|
||||||
|
print(count,line)
|
||||||
|
line = inFile.readline()
|
||||||
|
line = line.rstrip("\n")
|
||||||
|
count = count + 1
|
||||||
|
except:
|
||||||
|
print(f"The file {filename} cannot be accessed.")
|
||||||
|
sys.exit(-1)
|
||||||
|
|
||||||
|
|
@ -0,0 +1,29 @@
|
||||||
|
#!/usr/bin/python3
|
||||||
|
|
||||||
|
# See https://stackabuse.com/read-a-file-line-by-line-in-python/
|
||||||
|
# for more information
|
||||||
|
# Just try reading it line by line on the first attempt.
|
||||||
|
try:
|
||||||
|
inFile = open("dogs.csv",'r')
|
||||||
|
|
||||||
|
count = 1
|
||||||
|
line = inFile.readline()
|
||||||
|
line = line.rstrip("\n")
|
||||||
|
# process header
|
||||||
|
columnNames = line.split(",")
|
||||||
|
print(columnNames)
|
||||||
|
while(line): # Read line and place in variable named line
|
||||||
|
# print(count,line.rstrip("\n"))
|
||||||
|
print(count,line)
|
||||||
|
columns = line.split(",")
|
||||||
|
# print(columns)
|
||||||
|
counter = 0
|
||||||
|
while(counter < 4):
|
||||||
|
print("\t{:12s} {:>20s}".format(columnNames[counter],columns[counter]) )
|
||||||
|
counter = counter + 1
|
||||||
|
line = inFile.readline()
|
||||||
|
line = line.rstrip("\n")
|
||||||
|
count = count + 1
|
||||||
|
|
||||||
|
finally:
|
||||||
|
inFile.close()
|
||||||
|
|
@ -0,0 +1,22 @@
|
||||||
|
#!/usr/bin/python3
|
||||||
|
|
||||||
|
# See https://stackabuse.com/read-a-file-line-by-line-in-python/
|
||||||
|
# for more information
|
||||||
|
# Just try reading it line by line on the first attempt.
|
||||||
|
|
||||||
|
sampleData = ["Harry", "Colorado", "Shenanigans", "Mandy", "Rusty"]
|
||||||
|
|
||||||
|
try:
|
||||||
|
outFile = open("testdatawrite.txt",'w')
|
||||||
|
|
||||||
|
for dog in sampleData:
|
||||||
|
print(dog)
|
||||||
|
outFile.writelines(dog+"\n")
|
||||||
|
|
||||||
|
except:
|
||||||
|
print("File write error!")
|
||||||
|
exit(-1)
|
||||||
|
|
||||||
|
# When I get to the end of the file.
|
||||||
|
#finally:
|
||||||
|
outFile.close()
|
||||||
|
|
@ -0,0 +1,4 @@
|
||||||
|
Harry,2007
|
||||||
|
Shenanigans,2010
|
||||||
|
Katrina,2005
|
||||||
|
Mandy,2016
|
||||||
|
|
@ -0,0 +1,5 @@
|
||||||
|
Harry
|
||||||
|
Colorado
|
||||||
|
Shenanigans
|
||||||
|
Mandy
|
||||||
|
Rusty
|
||||||
|
|
@ -0,0 +1,5 @@
|
||||||
|
Harry
|
||||||
|
Colorado
|
||||||
|
Shenanigans
|
||||||
|
Mandy
|
||||||
|
Rusty
|
||||||
|
|
@ -0,0 +1,8 @@
|
||||||
|
|
||||||
|
data1 = float(input("Enter the dividend "))
|
||||||
|
|
||||||
|
data2 = float(input("Enter the divisor "))
|
||||||
|
|
||||||
|
quotient = data1/data2
|
||||||
|
|
||||||
|
print(f"{data1}/{data2} = {quotient}")
|
||||||
|
|
@ -0,0 +1,13 @@
|
||||||
|
import sys
|
||||||
|
|
||||||
|
data1 = float(input("Enter the dividend "))
|
||||||
|
|
||||||
|
data2 = float(input("Enter the divisor "))
|
||||||
|
|
||||||
|
try:
|
||||||
|
quotient = data1/data2
|
||||||
|
print(f"{data1}/{data2} = {quotient}")
|
||||||
|
except:
|
||||||
|
print(f"Invalid value. Division by zero is not allowed.")
|
||||||
|
sys.exit(-1)
|
||||||
|
|
||||||
|
|
@ -0,0 +1,20 @@
|
||||||
|
import sys
|
||||||
|
|
||||||
|
try:
|
||||||
|
data1 = float(input("Enter the dividend "))
|
||||||
|
except:
|
||||||
|
print(f"Invalid value for the dividend ")
|
||||||
|
sys.exit(-2)
|
||||||
|
try:
|
||||||
|
data2 = float(input("Enter the divisor "))
|
||||||
|
except:
|
||||||
|
print(f"Invalid value for the divisor ")
|
||||||
|
sys.exit(-3)
|
||||||
|
|
||||||
|
try:
|
||||||
|
quotient = data1/data2
|
||||||
|
print(f"{data1}/{data2} = {quotient}")
|
||||||
|
except:
|
||||||
|
print(f"Invalid value. Division by zero is not allowed.")
|
||||||
|
sys.exit(-1)
|
||||||
|
|
||||||
|
|
@ -0,0 +1,19 @@
|
||||||
|
import sys
|
||||||
|
|
||||||
|
def getFloatValue(message):
|
||||||
|
try:
|
||||||
|
data1 = float(input(message))
|
||||||
|
except:
|
||||||
|
print(f"Invalid value for a floating point number. ")
|
||||||
|
sys.exit(-2)
|
||||||
|
return data1
|
||||||
|
|
||||||
|
data1 = getFloatValue("Enter value for the dividend ")
|
||||||
|
data2 = getFloatValue("Enter value for the divisor ")
|
||||||
|
|
||||||
|
try:
|
||||||
|
quotient = data1/data2
|
||||||
|
print(f"{data1}/{data2} = {quotient}")
|
||||||
|
except:
|
||||||
|
print(f"Invalid value. Division by zero is not allowed.")
|
||||||
|
sys.exit(-1)
|
||||||
|
|
@ -0,0 +1,4 @@
|
||||||
|
# https://www.w3schools.io/file/csv-extension-introduction/
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
@ -0,0 +1,20 @@
|
||||||
|
import matplotlib.pyplot as plt
|
||||||
|
import numpy as np
|
||||||
|
|
||||||
|
plt.style.use('_mpl-gallery')
|
||||||
|
|
||||||
|
# Make data
|
||||||
|
n = 100
|
||||||
|
xs = np.linspace(0, 1, n)
|
||||||
|
ys = np.sin(xs * 6 * np.pi)
|
||||||
|
zs = np.cos(xs * 6 * np.pi)
|
||||||
|
|
||||||
|
# Plot
|
||||||
|
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
|
||||||
|
ax.plot(xs, ys, zs)
|
||||||
|
|
||||||
|
ax.set(xticklabels=[],
|
||||||
|
yticklabels=[],
|
||||||
|
zticklabels=[])
|
||||||
|
|
||||||
|
plt.show()
|
||||||
|
|
@ -0,0 +1,24 @@
|
||||||
|
import matplotlib.pyplot as plt
|
||||||
|
import numpy as np
|
||||||
|
|
||||||
|
plt.style.use('_mpl-gallery')
|
||||||
|
|
||||||
|
# make data
|
||||||
|
x = np.linspace(0, 10, 100)
|
||||||
|
y = 4 + 1 * np.sin(2 * x)
|
||||||
|
x2 = np.linspace(0, 10, 25)
|
||||||
|
y2 = 4 + 1 * np.sin(2 * x2)
|
||||||
|
|
||||||
|
print(x)
|
||||||
|
|
||||||
|
# plot
|
||||||
|
fig, ax = plt.subplots()
|
||||||
|
|
||||||
|
#ax.plot(x2, y2 + 2.5, 'x', markeredgewidth=2)
|
||||||
|
ax.plot(x, y, linewidth=2.0)
|
||||||
|
#ax.plot(x2, y2 - 2.5, 'o-', linewidth=2)
|
||||||
|
|
||||||
|
ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
|
||||||
|
ylim=(0, 8), yticks=np.arange(1, 8))
|
||||||
|
|
||||||
|
plt.show()
|
||||||
|
|
@ -0,0 +1,7 @@
|
||||||
|
# pip install matpplotlib
|
||||||
|
from matplotlib import pyplot as plt
|
||||||
|
labels = [ "Python", "Java", "HTML", "C#", "Javascript"]
|
||||||
|
data = [95,80,65,80,95]
|
||||||
|
explode = [0.0,0.0,0.1,0.0,0.0]
|
||||||
|
plt.pie(data, labels=labels, explode=explode)
|
||||||
|
plt.show()
|
||||||
|
|
@ -0,0 +1,51 @@
|
||||||
|
"""
|
||||||
|
================
|
||||||
|
Basic matplotlib
|
||||||
|
================
|
||||||
|
|
||||||
|
A basic example of 3D Graph visualization using `mpl_toolkits.mplot_3d`.
|
||||||
|
|
||||||
|
"""
|
||||||
|
|
||||||
|
import networkx as nx
|
||||||
|
import numpy as np
|
||||||
|
import matplotlib.pyplot as plt
|
||||||
|
from mpl_toolkits.mplot3d import Axes3D
|
||||||
|
|
||||||
|
# The graph to visualize
|
||||||
|
G = nx.cycle_graph(20)
|
||||||
|
|
||||||
|
# 3d spring layout
|
||||||
|
pos = nx.spring_layout(G, dim=3, seed=779)
|
||||||
|
# Extract node and edge positions from the layout
|
||||||
|
node_xyz = np.array([pos[v] for v in sorted(G)])
|
||||||
|
edge_xyz = np.array([(pos[u], pos[v]) for u, v in G.edges()])
|
||||||
|
|
||||||
|
# Create the 3D figure
|
||||||
|
fig = plt.figure()
|
||||||
|
ax = fig.add_subplot(111, projection="3d")
|
||||||
|
|
||||||
|
# Plot the nodes - alpha is scaled by "depth" automatically
|
||||||
|
ax.scatter(*node_xyz.T, s=100, ec="w")
|
||||||
|
|
||||||
|
# Plot the edges
|
||||||
|
for vizedge in edge_xyz:
|
||||||
|
ax.plot(*vizedge.T, color="tab:gray")
|
||||||
|
|
||||||
|
|
||||||
|
def _format_axes(ax):
|
||||||
|
"""Visualization options for the 3D axes."""
|
||||||
|
# Turn gridlines off
|
||||||
|
ax.grid(False)
|
||||||
|
# Suppress tick labels
|
||||||
|
for dim in (ax.xaxis, ax.yaxis, ax.zaxis):
|
||||||
|
dim.set_ticks([])
|
||||||
|
# Set axes labels
|
||||||
|
ax.set_xlabel("x")
|
||||||
|
ax.set_ylabel("y")
|
||||||
|
ax.set_zlabel("z")
|
||||||
|
|
||||||
|
|
||||||
|
_format_axes(ax)
|
||||||
|
fig.tight_layout()
|
||||||
|
plt.show()
|
||||||
|
|
@ -0,0 +1,8 @@
|
||||||
|
import numpy as np
|
||||||
|
from numpy import pi
|
||||||
|
np.linspace(0, 2, 9) # 9 numbers from 0 to 2
|
||||||
|
x = np.linspace(0, 2 * pi, 100) # useful to evaluate function at lots of points
|
||||||
|
f = np.sin(x)
|
||||||
|
|
||||||
|
print(x)
|
||||||
|
print(f)
|
||||||
Binary file not shown.
|
After Width: | Height: | Size: 96 KiB |
|
|
@ -0,0 +1,21 @@
|
||||||
|
import plotly.express as px
|
||||||
|
|
||||||
|
data = px.data.gapminder( )
|
||||||
|
|
||||||
|
fig = px.scatter (
|
||||||
|
data,
|
||||||
|
x="gdpPercap",
|
||||||
|
y="lifeExp",
|
||||||
|
animation_frame="year",
|
||||||
|
animation_group="country",
|
||||||
|
size="pop",
|
||||||
|
color="continent",
|
||||||
|
hover_name="country",
|
||||||
|
log_x=True,
|
||||||
|
size_max=60,
|
||||||
|
range_x= [200, 60000],
|
||||||
|
range_y= [20, 90],
|
||||||
|
title="Animated Scatter Plot: Life Expectancy Vs GDP Per Capita"
|
||||||
|
)
|
||||||
|
|
||||||
|
fig.show()
|
||||||
|
|
@ -0,0 +1,29 @@
|
||||||
|
import json
|
||||||
|
import urllib.request
|
||||||
|
import pprint
|
||||||
|
|
||||||
|
# See https://www.icndb.com
|
||||||
|
|
||||||
|
def get_joke():
|
||||||
|
|
||||||
|
url = "http://api.icndb.com/jokes/random?limitTo=nerdy "
|
||||||
|
|
||||||
|
response = urllib.request.urlopen(url)
|
||||||
|
result = json.loads(response.read())
|
||||||
|
|
||||||
|
# print(result)
|
||||||
|
|
||||||
|
return result
|
||||||
|
|
||||||
|
def prettyPrintDictionary(myDict):
|
||||||
|
pprint.pprint(myDict)
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
joke = get_joke()
|
||||||
|
|
||||||
|
#prettyPrintDictionary(joke)
|
||||||
|
|
||||||
|
print(joke['value']['joke'])
|
||||||
|
|
||||||
|
|
||||||
Binary file not shown.
|
After Width: | Height: | Size: 1.5 KiB |
|
|
@ -0,0 +1,6 @@
|
||||||
|
#!/bin/python3
|
||||||
|
|
||||||
|
import json
|
||||||
|
import turtle
|
||||||
|
import urllib.request
|
||||||
|
|
||||||
Binary file not shown.
|
After Width: | Height: | Size: 1.4 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 89 KiB |
|
|
@ -0,0 +1,44 @@
|
||||||
|
"""
|
||||||
|
========
|
||||||
|
Football
|
||||||
|
========
|
||||||
|
|
||||||
|
Load football network in GML format and compute some network statistcs.
|
||||||
|
|
||||||
|
Shows how to download GML graph in a zipped file, unpack it, and load
|
||||||
|
into a NetworkX graph.
|
||||||
|
|
||||||
|
Requires Internet connection to download the URL
|
||||||
|
http://www-personal.umich.edu/~mejn/netdata/football.zip
|
||||||
|
"""
|
||||||
|
|
||||||
|
import urllib.request
|
||||||
|
import io
|
||||||
|
import zipfile
|
||||||
|
|
||||||
|
import matplotlib.pyplot as plt
|
||||||
|
import networkx as nx
|
||||||
|
|
||||||
|
url = "http://www-personal.umich.edu/~mejn/netdata/football.zip"
|
||||||
|
|
||||||
|
sock = urllib.request.urlopen(url) # open URL
|
||||||
|
s = io.BytesIO(sock.read()) # read into BytesIO "file"
|
||||||
|
sock.close()
|
||||||
|
|
||||||
|
zf = zipfile.ZipFile(s) # zipfile object
|
||||||
|
txt = zf.read("football.txt").decode() # read info file
|
||||||
|
gml = zf.read("football.gml").decode() # read gml data
|
||||||
|
# throw away bogus first line with # from mejn files
|
||||||
|
gml = gml.split("\n")[1:]
|
||||||
|
G = nx.parse_gml(gml) # parse gml data
|
||||||
|
|
||||||
|
print(txt)
|
||||||
|
# print degree for each team - number of games
|
||||||
|
for n, d in G.degree():
|
||||||
|
print(f"{n:20} {d:2}")
|
||||||
|
|
||||||
|
options = {"node_color": "black", "node_size": 50, "linewidths": 0, "width": 0.1}
|
||||||
|
|
||||||
|
pos = nx.spring_layout(G, seed=1969) # Seed for reproducible layout
|
||||||
|
nx.draw(G, pos, **options)
|
||||||
|
plt.show()
|
||||||
Loading…
Reference in New Issue