You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
258 lines
9.9 KiB
258 lines
9.9 KiB
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "markdown",
|
|
"source": [
|
|
"## စွမ်းဆောင်ရည်နှင့် စာရင်းအင်းဆိုင်ရာ သဘောတရားအကြောင်း\n",
|
|
"## လုပ်ငန်းတာဝန်\n",
|
|
"\n",
|
|
"ဒီလုပ်ငန်းတာဝန်မှာ ကျွန်တော်တို့ [ဒီနေရာ](https://www4.stat.ncsu.edu/~boos/var.select/diabetes.html) မှ ယူထားတဲ့ ဆီးချိုရောဂါရှိသူများ၏ ဒေတာဆက်တင်ကို အသုံးပြုသွားမှာ ဖြစ်ပါတယ်။\n"
|
|
],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 13,
|
|
"source": [
|
|
"import pandas as pd\n",
|
|
"import numpy as np\n",
|
|
"\n",
|
|
"df = pd.read_csv(\"../../data/diabetes.tsv\",sep='\\t')\n",
|
|
"df.head()"
|
|
],
|
|
"outputs": [
|
|
{
|
|
"output_type": "execute_result",
|
|
"data": {
|
|
"text/plain": [
|
|
" AGE SEX BMI BP S1 S2 S3 S4 S5 S6 Y\n",
|
|
"0 59 2 32.1 101.0 157 93.2 38.0 4.0 4.8598 87 151\n",
|
|
"1 48 1 21.6 87.0 183 103.2 70.0 3.0 3.8918 69 75\n",
|
|
"2 72 2 30.5 93.0 156 93.6 41.0 4.0 4.6728 85 141\n",
|
|
"3 24 1 25.3 84.0 198 131.4 40.0 5.0 4.8903 89 206\n",
|
|
"4 50 1 23.0 101.0 192 125.4 52.0 4.0 4.2905 80 135"
|
|
],
|
|
"text/html": [
|
|
"<div>\n",
|
|
"<style scoped>\n",
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
|
" vertical-align: middle;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe tbody tr th {\n",
|
|
" vertical-align: top;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe thead th {\n",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>AGE</th>\n",
|
|
" <th>SEX</th>\n",
|
|
" <th>BMI</th>\n",
|
|
" <th>BP</th>\n",
|
|
" <th>S1</th>\n",
|
|
" <th>S2</th>\n",
|
|
" <th>S3</th>\n",
|
|
" <th>S4</th>\n",
|
|
" <th>S5</th>\n",
|
|
" <th>S6</th>\n",
|
|
" <th>Y</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>59</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>32.1</td>\n",
|
|
" <td>101.0</td>\n",
|
|
" <td>157</td>\n",
|
|
" <td>93.2</td>\n",
|
|
" <td>38.0</td>\n",
|
|
" <td>4.0</td>\n",
|
|
" <td>4.8598</td>\n",
|
|
" <td>87</td>\n",
|
|
" <td>151</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>48</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>21.6</td>\n",
|
|
" <td>87.0</td>\n",
|
|
" <td>183</td>\n",
|
|
" <td>103.2</td>\n",
|
|
" <td>70.0</td>\n",
|
|
" <td>3.0</td>\n",
|
|
" <td>3.8918</td>\n",
|
|
" <td>69</td>\n",
|
|
" <td>75</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>72</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>30.5</td>\n",
|
|
" <td>93.0</td>\n",
|
|
" <td>156</td>\n",
|
|
" <td>93.6</td>\n",
|
|
" <td>41.0</td>\n",
|
|
" <td>4.0</td>\n",
|
|
" <td>4.6728</td>\n",
|
|
" <td>85</td>\n",
|
|
" <td>141</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>24</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>25.3</td>\n",
|
|
" <td>84.0</td>\n",
|
|
" <td>198</td>\n",
|
|
" <td>131.4</td>\n",
|
|
" <td>40.0</td>\n",
|
|
" <td>5.0</td>\n",
|
|
" <td>4.8903</td>\n",
|
|
" <td>89</td>\n",
|
|
" <td>206</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>50</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>23.0</td>\n",
|
|
" <td>101.0</td>\n",
|
|
" <td>192</td>\n",
|
|
" <td>125.4</td>\n",
|
|
" <td>52.0</td>\n",
|
|
" <td>4.0</td>\n",
|
|
" <td>4.2905</td>\n",
|
|
" <td>80</td>\n",
|
|
" <td>135</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"execution_count": 13
|
|
}
|
|
],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"source": [
|
|
"ဒီဒေတာဆက်တင်ထဲမှာ ကော်လံတွေက အောက်ပါအတိုင်းဖြစ်ပါတယ်- \n",
|
|
"* အသက်နဲ့ လိင်က အလွယ်တကူနားလည်နိုင်ပါတယ် \n",
|
|
"* BMI က ကိုယ်အလေးချိန်နှင့် အရွယ်အစားညှိထားသော အညွှန်းကိန်းဖြစ်ပါတယ် \n",
|
|
"* BP က ပျမ်းမျှ သွေးဖိအား \n",
|
|
"* S1 ကနေ S6 အထိက သွေးစစ်ဆေးမှုအမျိုးမျိုး \n",
|
|
"* Y က တစ်နှစ်အတွင်း ရောဂါတိုးတက်မှုအရည်အချင်းအတိုင်းအတာ \n",
|
|
"\n",
|
|
"ဒီဒေတာဆက်တင်ကို သက်မှတ်နှုန်းနှင့် သင်္ချာဆိုင်ရာ နည်းလမ်းများကို အသုံးပြုပြီး လေ့လာကြမယ်။\n",
|
|
"\n",
|
|
"### တာဝန် ၁: တန်ဖိုးအားလုံးအတွက် ပျမ်းမျှနှုန်းနဲ့ မျိုးကွဲမှုကို တွက်ချက်ပါ \n"
|
|
],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"source": [],
|
|
"outputs": [],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"source": [],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"source": [],
|
|
"outputs": [],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"source": [],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"source": [],
|
|
"outputs": [],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"source": [
|
|
"### တာဝန် ၄: အမျိုးမျိုးသော အပြောင်းအလဲများနှင့် ရောဂါတိုးတက်မှု (Y) အကြား ဆက်စပ်မှုကို စမ်းသပ်ပါ\n",
|
|
"\n",
|
|
"> **အကြံပြုချက်** ဆက်စပ်မှုအချိုးဇယားသည် ဘယ်တန်ဖိုးများသည် အချင်းချင်းမူတည်နေသည်ကို အထောက်အကူဖြစ်စေမည့် အရေးကြီးသော အချက်အလက်များကို ပေးနိုင်ပါသည်။\n"
|
|
],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"source": [],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"source": [],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"source": [],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"\n---\n\n**ဝက်ဘ်ဆိုက်မှတ်ချက်**: \nဤစာရွက်စာတမ်းကို AI ဘာသာပြန်ဝန်ဆောင်မှု [Co-op Translator](https://github.com/Azure/co-op-translator) ကို အသုံးပြု၍ ဘာသာပြန်ထားပါသည်။ ကျွန်ုပ်တို့သည် တိကျမှန်ကန်မှုအတွက် ကြိုးစားနေပါသော်လည်း၊ အလိုအလျောက်ဘာသာပြန်မှုများတွင် အမှားများ သို့မဟုတ် မမှန်ကန်မှုများ ပါဝင်နိုင်သည်ကို ကျေးဇူးပြု၍ သတိပြုပါ။ မူရင်းစာရွက်စာတမ်းကို ၎င်း၏ မူလဘာသာစကားဖြင့် အာဏာတည်သောရင်းမြစ်အဖြစ် သတ်မှတ်သင့်ပါသည်။ အရေးကြီးသော အချက်အလက်များအတွက် လူကူးဘာသာပြန်မှုကို အကြံပြုပါသည်။ ဤဘာသာပြန်မှုကို အသုံးပြုခြင်းမှ ဖြစ်ပေါ်လာသော နားလည်မှုမှားများ သို့မဟုတ် အဓိပ္ပါယ်မှားများအတွက် ကျွန်ုပ်တို့သည် တာဝန်မယူပါ။\n"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"orig_nbformat": 4,
|
|
"language_info": {
|
|
"name": "python",
|
|
"version": "3.8.8",
|
|
"mimetype": "text/x-python",
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"pygments_lexer": "ipython3",
|
|
"nbconvert_exporter": "python",
|
|
"file_extension": ".py"
|
|
},
|
|
"kernelspec": {
|
|
"name": "python3",
|
|
"display_name": "Python 3.8.8 64-bit (conda)"
|
|
},
|
|
"interpreter": {
|
|
"hash": "86193a1ab0ba47eac1c69c1756090baa3b420b3eea7d4aafab8b85f8b312f0c5"
|
|
},
|
|
"coopTranslator": {
|
|
"original_hash": "6d945fd15163f60cb473dbfe04b2d100",
|
|
"translation_date": "2025-09-06T18:00:47+00:00",
|
|
"source_file": "1-Introduction/04-stats-and-probability/assignment.ipynb",
|
|
"language_code": "my"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
} |