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잠토의 잠망경
Splunk URL 추가 [https://community.splunk.com/t5/Dashboards-Visualizations/How-can-I-create-a-static-link-to-an-external-url-on-a-dashboard/m-p/145202] Google gym [https://m.blog.naver.com/sonmh12/222036705425] MountainCar-v0 [http://jinicoding.net/openai-gym%EC%9C%BC%EB%A1%9C-q-table-%EC%95%8C%EA%B3%A0%EB%A6%AC%EC%A6%98-%EB%A7%8C%EB%93%A4%EA%B8%B0-2/] 좀더 쉽게 설명 되어 있음 추천 mariadb index 생성 [https://m..
오류 상황 단일 값에 대하여 DataFrame을 만드는 경우 def sample01(): ''' 모든 값이 scaler인 경우 오류 :return: ''' import pandas as pd from pandas import DataFrame datas:DataFrame = pd.DataFrame({'col1':2, 'col2':1}) # ValueError: If using all scalar values, you must pass an index print(datas) solution 1 index를 지정한다. github def sample02(): ''' 모든 값이 scaler인 경우 :return: ''' import pandas as pd from pandas import DataFrame d..
간략 1. splunk 수신 설정 port: 9997 2. Search - Index 설정 3. Search - Source Type 설정 4. Forwarder - Indexer 설정 C:\Program Files\SplunkUniversalForwarder\etc\system\local\outputs.conf [tcpout] defaultGroup = default-autolb-group [tcpout:default-autolb-group] server = 192.168.131.133:9997,127.0.0.1:9997 [tcpout-server://192.168.131.133:9997] [tcpout-server://127.0.0.1:9997] 5. Forwarder - Directory(Path)..
nonzero array중 0 이 아닌 index를 얻고자할때 사용한다. 1차원 import numpy as np a = np.array([0,1,2,3,4,5,0,1,2,3,4]) nonzeroList = a.nonzero() print(nonzeroList) #[1,2,3,4,5,7,8,9,10], dtype=int64 2차원 import numpy as np b = np.array([0,1,2,3,0],[0,1,2,3,0]) print(b.nonzero()) # [0,0,0,1,1,1] # [1,2,3,1,2,3] print(np.transpose(b.nonzero())) # merge
DataFrame에서 Series 추출(loc) loc 속성을 이용하여 원하는 index를 지정후 추출 import pandas as pd from collections import OrderedDict s = pd.DataFrame({ 'Address':['Seoul','Asan'], 'occupation':['doctor','IT'], 'Born':['1981-01-10','1999-11-02'], 'Died':['2100-01-10','2099-01-02'], 'Age':[40,20]}, index=['a&#..
Series 만들기 가장 단순한 방식, index 지정 안함 import pandas as pd s = pd.Series(['a',42]) print(s) print(type(s)) output >>> print(s) 0 a 1 42 dtype: object >>> print(type(s)) Series 만들기, index를 지정 import pandas as pd s = pd.Series(['a',42],index=['name','age']) print(s) print(type(s)) output >>> print(s) name a age 42 dtype: object >>> print(type(s)) DataFrame 만들기 import pan..