numpy 또는 pandas를 사용하여 긴 형식의 CSV 파일 조작

Question

더 많은 분석을 수행 할 수 있도록 간단한 스크립트를 작성하여 포트란 코드의 CSV 출력 파일을 팬더 DataFrame 개체로 변환하려고합니다. csv에는 두 개의 열이 있지만 모양이 [n, 2] 인 데이터의 여러 추가 블록으로 구성됩니다 (각 샘플 이름의 형식은 RN_x입니다). 지금까지 다음 코드가 있지만 결과 DataFrame 개체는 분석을 허용하지 않습니다. 아래 샘플 파일 (원본에서 많이 줄임)을 첨부했습니다. 덧붙여서 데이터 파일의 첫 번째 열은 날짜를 의미하지만 출력은 si = imulation의 하루에 해당하는 숫자입니다. 모든 조언을 많이 주시면 감사하겠습니다.

import numpy as np 
import pandas as pd 
import csv as csv 
readdata = csv.reader(open('C:/data/Test.csv', 'r')) 
data = [] 
for row in readdata: 
    data.append(row) 
a = np.array(data).reshape(11,-1, order = 'F') 
col = a[0,:4].reshape(4) 
row = pd.Index(a[4:,0:1].reshape(7)) 
b = a[4:,5:] 
df = pd.DataFrame(b, index = row, columns = col) 

샘플 :

RN_48865, 
1,Observed 
1,0 
259,Computed 
1,0.000014 
91,0.000014 
182,0.000014 
274,0.000014 
366,0.000014 
457,0.000014 
548,0.000014 
RN_7445, 
1,Observed 
1,0 
259,Computed 
1,0.000013 
91,0.000013 
182,0.000013 
274,0.000013 
366,0.000013 
457,0.000013 
548,0.000013 
RN_9288, 
1,Observed 
1,0 
259,Computed 
1,0.000011 
91,0.000011 
182,0.000011 
274,0.000011 
366,0.000011 
457,0.000011 
548,0.000011 
RN_10955, 
1,Observed 
1,0 
259,Computed 
1,0.000014 
91,0.000014 
182,0.000014 
274,0.000014 
366,0.000014 
457,0.000014 
548,0.000014 

샘플 출력 :

Index,RN_48865,RN_7445,RN_9288,RN_10955 
1,0.000014,0.000013,0.000011,0.000014 
91,0.000014,0.000013,0.000011,0.000014 
182,0.000014,0.000013,0.000011,0.000014 
274,0.000014,0.000013,0.000011,0.000014 
366,0.000014,0.000013,0.000011,0.000014 
457,0.000014,0.000013,0.000011,0.000014 
548,0.000014,0.000013,0.000011,0.000014 

Answer 1

당신은 실제로 몇 가지 질문을 요구하고있다. 이것은 내가 원하는 출력에서 ​​이해할 수있는 것입니다 :

source="""RN_48865, 
    1,Observed 
    1,0 
    259,Computed 
    1,0.000014 
    91,0.000014 
    182,0.000014 
    274,0.000014 
    366,0.000014 
    457,0.000014 
    548,0.000014 
    RN_7445, 
    1,Observed 
    1,0 
    259,Computed 
    1,0.000013 
    91,0.000013 
    182,0.000013 
    274,0.000013 
    366,0.000013 
    457,0.000013 
    548,0.000013 
    RN_9288, 
    1,Observed 
    1,0 
    259,Computed 
    1,0.000011 
    91,0.000011 
    182,0.000011 
    274,0.000011 
    366,0.000011 
    457,0.000011 
    548,0.000011 
    RN_10955, 
    1,Observed 
    1,0 
    259,Computed 
    1,0.000014 
    91,0.000014 
    182,0.000014 
    274,0.000014 
    366,0.000014 
    457,0.000014 
    548,0.000014 
""" 
import pandas as pd 
import numpy as np 
import StringIO 
df = pd.read_csv(StringIO.StringIO(source), header=None) 
rns = np.where(df[0].apply(lambda x: x.lstrip().startswith('RN_')))[0] 
length = rns[1] - rns[0] 
index = df[0].iloc[4:length] 
cols = df[0][::length].apply(lambda x: x.lstrip()).values 
result_df = pd.DataFrame(index=index) 
for col_num, col_start in enumerate(range(0, len(df), length)): 
    result_df[cols[col_num]] = df[1][col_num*length+4 : (col_num+1)*length].values 
print result_df 

출력 : 날짜

 RN_48865 RN_7445 RN_9288 RN_10955 
1 0.000014 0.000013 0.000011 0.000014 
91 0.000014 0.000013 0.000011 0.000014 
182 0.000014 0.000013 0.000011 0.000014 
274 0.000014 0.000013 0.000011 0.000014 
366 0.000014 0.000013 0.000011 0.000014 
457 0.000014 0.000013 0.000011 0.000014 
548 0.000014 0.000013 0.000011 0.000014 

사용 :

pandas.read_csv('file', 
    parse_date=0, # 0th column 
    date_parser=lambda x: pandas.Timestamp('1995-1-1')+timedelta(x))