因此,我有几个表示某些数据的 csv文件,每个文件可能有不同的初始注释行
table_doi: 10.17182/hepdata.52402.v1/t7
name: Table 7
...
ABS(YRAP), < 0.1
SQRT(S) [GeV], 1960
PT [GEV], PT [GEV] LOW, PT [GEV] HIGH, D2(SIG)/DYRAP/DPT [NB/GEV]
67, 62, 72, 6.68
...
613.5, 527, 700, 1.81E-07
我只想读入相关的数据和它们的标题,它们是从一行开始的
PT [GEV], PT [GEV] LOW, PT [GEV] HIGH, D2(SIG)/DYRAP/DPT [NB/GEV]
因此,我会想到的策略是找到模式PT [GEV]
并从那里开始阅读。
然而,我不确定如何在Python中实现这一点,有人能在这方面帮助我吗?
提前谢谢你!
顺便说一句,我目前拥有的函数是
import os
import glob
import csv
def read_multicolumn_csv_files_into_dictionary(folderpath, dictionary):
filepath = folderpath + '*.csv'
files = sorted(glob.glob(filepath))
for file in files:
data_set = file.replace(folderpath, '').replace('.csv', '')
dictionary[data_set] = {}
with open(file, 'r') as data_file:
data_pipe = csv.DictReader(data_file)
dictionary[data_set]['pt'] = []
dictionary[data_set]['sigma'] = []
for row in data_pipe:
dictionary[data_set]['pt'].append(float(row['PT [GEV]']))
dictionary[data_set]['sigma'].append(float(row['D2(SIG)/DYRAP/DPT [NB/GEV]']))
return dictionary
这只有在我手动删除csv文件中的那些初始注释时才起作用。
发布于 2019-01-15 14:02:42
假设每个文件都有一行以PT [GEV]
开头
import os
import pandas as pd
...
csvs = []
for file in files:
with open(file) as f:
for i, l in enumerate(f):
if l.startswith('PT [GEV]'):
csvs.append(pd.read_csv(file, skiprows = i))
break
df = pd.concat(csvs)
发布于 2019-01-15 14:17:35
查看startswith
。另外,你可以在这里找到详细的解释。https://cmdlinetips.com/2018/01/3-ways-to-read-a-file-and-skip-initial-comments-in-python/
发布于 2019-01-15 14:14:50
尝试这样做,它将搜索包含PT [GEV]
的行,如果找到包含,它会将m
更改为true,并开始将剩余的日期附加到列表中:
import csv
contain= 'PT [GEV]'
List=[]
m=false
with open('Users.csv', 'rt') as f:
reader = csv.reader(f, delimiter=',')
for row in reader:
for field in row:
if field == contain:
m=true
if m==true:
List.append(row)
https://stackoverflow.com/questions/54192970
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