Test page

Hello world

https://velog.io/@kwonhl0211/Hello-Kaggle-%EC%BA%90%EA%B8%80%EC%9D%B4-%EC%B2%98%EC%9D%8C%EC%9D%B8-%EB%B6%84%EB%93%A4%EC%9D%84-%EC%9C%84%ED%95%9C-%EC%BA%90%EA%B8%80-%EA%B0%80%EC%9D%B4%EB%93%9C

kaggle guide ko!!

https://medium.com/@kaggleteam/how-to-get-started-with-data-science-in-containers-6ed48cb08266

Kaggle note랑 연동 하는 방법이 나와 있는듯
나중에 Posting 해 봐야지 ^^

https://www.chartjs.org/docs/latest/samples/bar/horizontal.html

chart에대해 많은 List가 있는데 완전 유용할듯

neo4j 를 이용하여 graph 만들수 있다.

neo4j

git blog: Hexo로 multi, push

git config --global user.email "ssiasoda@gmil.com"
git config --global user.name "YoonHwa-P"


git push origin HEAD:main

내가 push 할때 쓰려고 저장

Kaggle/competitions
kaggle competition에 참가 할 수 있다.

!pip install kaggle

Requirement already satisfied: kaggle in /usr/local/lib/python3.7/dist-packages (1.5.12)
Requirement already satisfied: python-dateutil in /usr/local/lib/python3.7/dist-packages (from kaggle) (2.8.2)
Requirement already satisfied: urllib3 in /usr/local/lib/python3.7/dist-packages (from kaggle) (1.24.3)
Requirement already satisfied: six>=1.10 in /usr/local/lib/python3.7/dist-packages (from kaggle) (1.15.0)
Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from kaggle) (2.23.0)
Requirement already satisfied: python-slugify in /usr/local/lib/python3.7/dist-packages (from kaggle) (5.0.2)
Requirement already satisfied: certifi in /usr/local/lib/python3.7/dist-packages (from kaggle) (2021.5.30)
Requirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (from kaggle) (4.62.3)
Requirement already satisfied: text-unidecode>=1.3 in /usr/local/lib/python3.7/dist-packages (from python-slugify->kaggle) (1.3)
Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->kaggle) (3.0.4)
Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->kaggle) (2.10)

from google.colab import files

uploaded = files.upload()

for fn in uploaded.keys():
  print('User uploaded file "{name}" with length {length} bytes'.format(
      name=fn, length=len(uploaded[fn])))
  
# Then move kaggle.json into the folder where the API expects to find it.
!mkdir -p ~/.kaggle/ && mv kaggle.json ~/.kaggle/ && chmod 600 ~/.kaggle/kaggle.json

Upload widget is only available when the cell has been executed in the
current browser session. Please rerun this cell to enable.

---------------------------------------------------------------------------

KeyboardInterrupt                         Traceback (most recent call last)

<ipython-input-57-5e2b5f92ba05> in <module>()
      1 from google.colab import files
      2 
----> 3 uploaded = files.upload()
      4 
      5 for fn in uploaded.keys():


/usr/local/lib/python3.7/dist-packages/google/colab/files.py in upload()
     62   result = _output.eval_js(
     63       'google.colab._files._uploadFiles("{input_id}", "{output_id}")'.format(
---> 64           input_id=input_id, output_id=output_id))
     65   files = _collections.defaultdict(_six.binary_type)
     66   # Mapping from original filename to filename as saved locally.


/usr/local/lib/python3.7/dist-packages/google/colab/output/_js.py in eval_js(script, ignore_result, timeout_sec)
     38   if ignore_result:
     39     return
---> 40   return _message.read_reply_from_input(request_id, timeout_sec)
     41 
     42 


/usr/local/lib/python3.7/dist-packages/google/colab/_message.py in read_reply_from_input(message_id, timeout_sec)
     99     reply = _read_next_input_message()
    100     if reply == _NOT_READY or not isinstance(reply, dict):
--> 101       time.sleep(0.025)
    102       continue
    103     if (reply.get('type') == 'colab_reply' and


KeyboardInterrupt: 

데이터 다운로드 및 불러오기

!kaggle competitions list

Warning: Looks like you're using an outdated API Version, please consider updating (server 1.5.12 / client 1.5.4)
ref                                            deadline             category            reward  teamCount  userHasEntered  
---------------------------------------------  -------------------  ---------------  ---------  ---------  --------------  
contradictory-my-dear-watson                   2030-07-01 23:59:00  Getting Started     Prizes         63           False  
gan-getting-started                            2030-07-01 23:59:00  Getting Started     Prizes         81           False  
store-sales-time-series-forecasting            2030-06-30 23:59:00  Getting Started  Knowledge        487           False  
tpu-getting-started                            2030-06-03 23:59:00  Getting Started  Knowledge        157           False  
digit-recognizer                               2030-01-01 00:00:00  Getting Started  Knowledge       1459           False  
titanic                                        2030-01-01 00:00:00  Getting Started  Knowledge      14879           False  
house-prices-advanced-regression-techniques    2030-01-01 00:00:00  Getting Started  Knowledge       4418            True  
connectx                                       2030-01-01 00:00:00  Getting Started  Knowledge        263           False  
nlp-getting-started                            2030-01-01 00:00:00  Getting Started  Knowledge       1321           False  
competitive-data-science-predict-future-sales  2022-12-31 23:59:00  Playground           Kudos      12891           False  
g-research-crypto-forecasting                  2022-02-01 23:59:00  Featured          $125,000        148           False  
petfinder-pawpularity-score                    2022-01-13 23:59:00  Research           $25,000       1631           False  
optiver-realized-volatility-prediction         2022-01-10 23:59:00  Featured          $100,000       3852           False  
nfl-big-data-bowl-2022                         2022-01-06 23:59:00  Analytics         $100,000          0           False  
sartorius-cell-instance-segmentation           2021-12-30 23:59:00  Featured           $75,000        495           False  
wikipedia-image-caption                        2021-12-09 11:59:00  Playground            Swag         71           False  
lux-ai-2021                                    2021-12-06 23:59:00  Featured           $10,000        928           False  
tabular-playground-series-nov-2021             2021-11-30 23:59:00  Playground            Swag        352           False  
kaggle-survey-2021                             2021-11-28 23:59:00  Analytics          $30,000          0           False  
chaii-hindi-and-tamil-question-answering       2021-11-15 23:59:00  Research           $10,000        807           False  

!kaggle competitions download -c house-prices-advanced-regression-techniques

User cancelled operation

import pandas as pd 
train = pd.read_csv('train.csv')
test = pd.read_csv('test.csv')
print('Data Loading is done!')

Data Loading is done!

데이터 둘러보기

print("The shape of Train Data is:", train.shape)
print("The shape of Test Data is:", test.shape)

The shape of Train Data is: (1460, 81)
The shape of Test Data is: (1459, 80)

print(train.info())

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 1460 entries, 0 to 1459
Data columns (total 81 columns):
 #   Column         Non-Null Count  Dtype  
---  ------         --------------  -----  
 0   Id             1460 non-null   int64  
 1   MSSubClass     1460 non-null   int64  
 2   MSZoning       1460 non-null   object 
 3   LotFrontage    1201 non-null   float64
 4   LotArea        1460 non-null   int64  
 5   Street         1460 non-null   object 
 6   Alley          91 non-null     object 
 7   LotShape       1460 non-null   object 
 8   LandContour    1460 non-null   object 
 9   Utilities      1460 non-null   object 
 10  LotConfig      1460 non-null   object 
 11  LandSlope      1460 non-null   object 
 12  Neighborhood   1460 non-null   object 
 13  Condition1     1460 non-null   object 
 14  Condition2     1460 non-null   object 
 15  BldgType       1460 non-null   object 
 16  HouseStyle     1460 non-null   object 
 17  OverallQual    1460 non-null   int64  
 18  OverallCond    1460 non-null   int64  
 19  YearBuilt      1460 non-null   int64  
 20  YearRemodAdd   1460 non-null   int64  
 21  RoofStyle      1460 non-null   object 
 22  RoofMatl       1460 non-null   object 
 23  Exterior1st    1460 non-null   object 
 24  Exterior2nd    1460 non-null   object 
 25  MasVnrType     1452 non-null   object 
 26  MasVnrArea     1452 non-null   float64
 27  ExterQual      1460 non-null   object 
 28  ExterCond      1460 non-null   object 
 29  Foundation     1460 non-null   object 
 30  BsmtQual       1423 non-null   object 
 31  BsmtCond       1423 non-null   object 
 32  BsmtExposure   1422 non-null   object 
 33  BsmtFinType1   1423 non-null   object 
 34  BsmtFinSF1     1460 non-null   int64  
 35  BsmtFinType2   1422 non-null   object 
 36  BsmtFinSF2     1460 non-null   int64  
 37  BsmtUnfSF      1460 non-null   int64  
 38  TotalBsmtSF    1460 non-null   int64  
 39  Heating        1460 non-null   object 
 40  HeatingQC      1460 non-null   object 
 41  CentralAir     1460 non-null   object 
 42  Electrical     1459 non-null   object 
 43  1stFlrSF       1460 non-null   int64  
 44  2ndFlrSF       1460 non-null   int64  
 45  LowQualFinSF   1460 non-null   int64  
 46  GrLivArea      1460 non-null   int64  
 47  BsmtFullBath   1460 non-null   int64  
 48  BsmtHalfBath   1460 non-null   int64  
 49  FullBath       1460 non-null   int64  
 50  HalfBath       1460 non-null   int64  
 51  BedroomAbvGr   1460 non-null   int64  
 52  KitchenAbvGr   1460 non-null   int64  
 53  KitchenQual    1460 non-null   object 
 54  TotRmsAbvGrd   1460 non-null   int64  
 55  Functional     1460 non-null   object 
 56  Fireplaces     1460 non-null   int64  
 57  FireplaceQu    770 non-null    object 
 58  GarageType     1379 non-null   object 
 59  GarageYrBlt    1379 non-null   float64
 60  GarageFinish   1379 non-null   object 
 61  GarageCars     1460 non-null   int64  
 62  GarageArea     1460 non-null   int64  
 63  GarageQual     1379 non-null   object 
 64  GarageCond     1379 non-null   object 
 65  PavedDrive     1460 non-null   object 
 66  WoodDeckSF     1460 non-null   int64  
 67  OpenPorchSF    1460 non-null   int64  
 68  EnclosedPorch  1460 non-null   int64  
 69  3SsnPorch      1460 non-null   int64  
 70  ScreenPorch    1460 non-null   int64  
 71  PoolArea       1460 non-null   int64  
 72  PoolQC         7 non-null      object 
 73  Fence          281 non-null    object 
 74  MiscFeature    54 non-null     object 
 75  MiscVal        1460 non-null   int64  
 76  MoSold         1460 non-null   int64  
 77  YrSold         1460 non-null   int64  
 78  SaleType       1460 non-null   object 
 79  SaleCondition  1460 non-null   object 
 80  SalePrice      1460 non-null   int64  
dtypes: float64(3), int64(35), object(43)
memory usage: 924.0+ KB
None

print(test.info())

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 1459 entries, 0 to 1458
Data columns (total 80 columns):
 #   Column         Non-Null Count  Dtype  
---  ------         --------------  -----  
 0   Id             1459 non-null   int64  
 1   MSSubClass     1459 non-null   int64  
 2   MSZoning       1455 non-null   object 
 3   LotFrontage    1232 non-null   float64
 4   LotArea        1459 non-null   int64  
 5   Street         1459 non-null   object 
 6   Alley          107 non-null    object 
 7   LotShape       1459 non-null   object 
 8   LandContour    1459 non-null   object 
 9   Utilities      1457 non-null   object 
 10  LotConfig      1459 non-null   object 
 11  LandSlope      1459 non-null   object 
 12  Neighborhood   1459 non-null   object 
 13  Condition1     1459 non-null   object 
 14  Condition2     1459 non-null   object 
 15  BldgType       1459 non-null   object 
 16  HouseStyle     1459 non-null   object 
 17  OverallQual    1459 non-null   int64  
 18  OverallCond    1459 non-null   int64  
 19  YearBuilt      1459 non-null   int64  
 20  YearRemodAdd   1459 non-null   int64  
 21  RoofStyle      1459 non-null   object 
 22  RoofMatl       1459 non-null   object 
 23  Exterior1st    1458 non-null   object 
 24  Exterior2nd    1458 non-null   object 
 25  MasVnrType     1443 non-null   object 
 26  MasVnrArea     1444 non-null   float64
 27  ExterQual      1459 non-null   object 
 28  ExterCond      1459 non-null   object 
 29  Foundation     1459 non-null   object 
 30  BsmtQual       1415 non-null   object 
 31  BsmtCond       1414 non-null   object 
 32  BsmtExposure   1415 non-null   object 
 33  BsmtFinType1   1417 non-null   object 
 34  BsmtFinSF1     1458 non-null   float64
 35  BsmtFinType2   1417 non-null   object 
 36  BsmtFinSF2     1458 non-null   float64
 37  BsmtUnfSF      1458 non-null   float64
 38  TotalBsmtSF    1458 non-null   float64
 39  Heating        1459 non-null   object 
 40  HeatingQC      1459 non-null   object 
 41  CentralAir     1459 non-null   object 
 42  Electrical     1459 non-null   object 
 43  1stFlrSF       1459 non-null   int64  
 44  2ndFlrSF       1459 non-null   int64  
 45  LowQualFinSF   1459 non-null   int64  
 46  GrLivArea      1459 non-null   int64  
 47  BsmtFullBath   1457 non-null   float64
 48  BsmtHalfBath   1457 non-null   float64
 49  FullBath       1459 non-null   int64  
 50  HalfBath       1459 non-null   int64  
 51  BedroomAbvGr   1459 non-null   int64  
 52  KitchenAbvGr   1459 non-null   int64  
 53  KitchenQual    1458 non-null   object 
 54  TotRmsAbvGrd   1459 non-null   int64  
 55  Functional     1457 non-null   object 
 56  Fireplaces     1459 non-null   int64  
 57  FireplaceQu    729 non-null    object 
 58  GarageType     1383 non-null   object 
 59  GarageYrBlt    1381 non-null   float64
 60  GarageFinish   1381 non-null   object 
 61  GarageCars     1458 non-null   float64
 62  GarageArea     1458 non-null   float64
 63  GarageQual     1381 non-null   object 
 64  GarageCond     1381 non-null   object 
 65  PavedDrive     1459 non-null   object 
 66  WoodDeckSF     1459 non-null   int64  
 67  OpenPorchSF    1459 non-null   int64  
 68  EnclosedPorch  1459 non-null   int64  
 69  3SsnPorch      1459 non-null   int64  
 70  ScreenPorch    1459 non-null   int64  
 71  PoolArea       1459 non-null   int64  
 72  PoolQC         3 non-null      object 
 73  Fence          290 non-null    object 
 74  MiscFeature    51 non-null     object 
 75  MiscVal        1459 non-null   int64  
 76  MoSold         1459 non-null   int64  
 77  YrSold         1459 non-null   int64  
 78  SaleType       1458 non-null   object 
 79  SaleCondition  1459 non-null   object 
dtypes: float64(11), int64(26), object(43)
memory usage: 912.0+ KB
None