파이썬 초보 Pandas에서 인덱스 행 추가어떻게해야할까요?
조회수 290회
iloc등 해당내용이아닌
순수 데이터만 있고, 불러 들였을때 최상단 인덱스가 데이터 값이 아닌 0,1,2,3,4…와 같은 베이직 인덱스를 넣고싶습니다..
header 명령어를 쓰면되는데 맞을까요?
1 답변
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>>> import pandas as pd >>> import numpy as np >>> df = pd.util.testing.makeDataFrame() >>> df A B C D SIGmzXtCmx 0.470768 -0.807193 0.468051 0.488866 E3IKjzhosa -0.236880 -0.888015 -1.600056 -0.199805 lD7Ht3xkVP -0.193062 0.322076 -1.094081 0.582686 7q5Brj9AeQ -1.361694 -1.420203 -1.140609 -1.733826 Ojwcgiv4n0 -0.727904 -0.149616 0.971487 -0.534119 liAo28WDHV -1.884758 1.971477 -0.435113 -0.373316 ynChzER1cX 1.933783 0.460862 1.399503 0.850038 tkk5R6susD 1.072193 -0.883758 1.023936 -0.336794 DjOYPTEpsQ 0.621182 0.536783 0.800621 0.698601 PwZWRLp0nx -0.773563 -0.621115 -0.731001 -0.550074 aCXd4qbqIE -0.217936 0.402844 -0.182283 0.975230 PwL0VM1tA5 0.658788 1.239632 1.545079 0.493019 4JaTLCc42P 0.816992 0.603847 -0.453202 -1.096263 wYYuleUYGh 0.986658 1.271412 -0.427188 -0.084533 D2Ip7GZsUM 1.206546 -0.844979 -0.486307 -0.245169 CqQuk6SnnD -0.004026 0.224801 0.345854 1.917603 AxdW5Lr344 0.667752 -0.241325 0.831370 -0.746942 BYCczu7eNB -1.308622 -0.761518 -0.618947 0.495343 Red66rCMCD -1.186703 0.771694 -0.973173 -0.295230 W2JwIPenhL 1.140977 -1.138799 -0.900574 2.199128 Rgt6LLWqMJ 1.236587 0.546710 -0.172605 -0.553494 zpoOSKvHL9 -0.124489 0.707197 -0.997226 -1.298666 SHEhdSCuS3 0.287685 -1.249335 -0.415259 -0.156002 xkvdqJFapJ 1.392805 -0.291524 0.464281 0.003749 lnXyD12sVF -1.280195 -2.139832 0.017224 -0.502024 2CTYCniPfH -0.387830 0.960747 -2.074247 0.252334 DWm73dPY4y 0.083914 -0.523869 -0.961064 1.735112 5I3apS1Y3T -0.115769 1.869465 -1.615079 1.480948 i8HWgP7qCy 1.184549 0.086129 -1.461264 1.682370 lHX2TkmWtq 0.792383 1.170700 -0.969357 -0.392937 >>> df = df.set_index(np.array(range(len(df)))+1) >>> df A B C D 1 0.470768 -0.807193 0.468051 0.488866 2 -0.236880 -0.888015 -1.600056 -0.199805 3 -0.193062 0.322076 -1.094081 0.582686 4 -1.361694 -1.420203 -1.140609 -1.733826 5 -0.727904 -0.149616 0.971487 -0.534119 6 -1.884758 1.971477 -0.435113 -0.373316 7 1.933783 0.460862 1.399503 0.850038 8 1.072193 -0.883758 1.023936 -0.336794 9 0.621182 0.536783 0.800621 0.698601 10 -0.773563 -0.621115 -0.731001 -0.550074 11 -0.217936 0.402844 -0.182283 0.975230 12 0.658788 1.239632 1.545079 0.493019 13 0.816992 0.603847 -0.453202 -1.096263 14 0.986658 1.271412 -0.427188 -0.084533 15 1.206546 -0.844979 -0.486307 -0.245169 16 -0.004026 0.224801 0.345854 1.917603 17 0.667752 -0.241325 0.831370 -0.746942 18 -1.308622 -0.761518 -0.618947 0.495343 19 -1.186703 0.771694 -0.973173 -0.295230 20 1.140977 -1.138799 -0.900574 2.199128 21 1.236587 0.546710 -0.172605 -0.553494 22 -0.124489 0.707197 -0.997226 -1.298666 23 0.287685 -1.249335 -0.415259 -0.156002 24 1.392805 -0.291524 0.464281 0.003749 25 -1.280195 -2.139832 0.017224 -0.502024 26 -0.387830 0.960747 -2.074247 0.252334 27 0.083914 -0.523869 -0.961064 1.735112 28 -0.115769 1.869465 -1.615079 1.480948 29 1.184549 0.086129 -1.461264 1.682370 30 0.792383 1.170700 -0.969357 -0.392937
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