我有要分析和绘图的csv文件(制表符分隔)。我可以从文件中提取数据,但是我更愿意通过使用列标题名而不是常规索引来做到这一点。
即代替:
freq_data = my_data[:,0]
我会用类似的东西:
freq2_data=dataA['Freq']
这将只给我那一列数据,顶部字段不带“ nan”。如果某些人对数据的排序不同,我想这样做。
我目前拥有的是:
import os
import csv
import numpy as np
from numpy import genfromtxt
def mylistdir(directory):
"""A specialized version of os.listdir() that ignores files that
start with a leading period."""
filelist = os.listdir(directory)
return [x for x in filelist
if not (x.startswith('.'))]
path = ("C:\\Users\\priper\\Desktop\\rough_data\\")
results_files = mylistdir(path)
print(results_files)
vel_data = []
for f in results_files:
f = path + f
my_data = np.genfromtxt(f, dtype = float, delimiter='\t') #, names = True, max_rows=1
print(my_data)
freq_data = my_data[:,0]
height_data = my_data[:,1]
width_data = my_data[:,2]
time_data = my_data[:,3]
freq2_data=dataA['Freq']
print(width_data)
print(freq2_data)
关于我能做什么的任何想法?
csv文件:
Freqheight_cmsWidth_cmsTime_secs
"998.2121573301549 44.08897100772889 6.445672191528545 90.0"
"998.2121573301549 46.34952337794475 6.49171270718232 90.0"
"998.2121573301549 39.7907973252776 6.49171270718232 90.0"
"1999.404052443385 42.986804623146725 6.445672191528545 90.0"
"1999.404052443385 38.76177273904744 6.49171270718232 90.0"
"1999.404052443385 46.34952337794475 6.491875969369261 89.59365376669096"
"2997.61620977354 44.08897100772889 6.491875969369261 89.59365376669096"
"2997.61620977354 42.986804623146725 6.537915335317934 89.59651526494126"
"2997.61620977354 44.08897100772889 6.49171270718232 90.0"
"3998.80810488677 47.50820176059876 6.307550644567219 90.0"
"3998.80810488677 46.34952337794475 6.3535911602209945 90.0"
"3998.80810488677 41.903151251584184 6.3997972870975675 89.58780725859766"
"5000.0 38.76177273904744 6.21564013134898 89.57559458063852"
"5000.0 44.08897100772889 6.261510128913444 90.0"
"5000.0 41.903151251584184 6.2616793932272925 89.57871509583141"
"5998.212157330155 33.881963382336906 6.077522459688805 89.5659493678606"
"5998.212157330155 47.50820176059876 5.985444111277719 89.55927192723898"
"5998.212157330155 53.59203690324092 6.123388581952118 90.0"
这是仔细阅读以下用户给出的答案和提示后起作用的方法。
for f in results_files:
f = path + f
data = pd.read_csv(f, sep = '\t')
length_of_data = len(data)
print(data.head(length_of_data))
freqy = data[['Freq']]
print(freqy)
使用 pandas 库:https : //pandas.pydata.org/pandas-docs/version/0.23.4/genic/pandas.read_csv.html
import pandas as pd
my_csv = pd.read_csv(filepath, header, names)
“标题:整数或整数列表,默认为'推断'
行号(用作列名)以及数据的开头。默认行为是推断列名:如果未传递名称,则行为与header = 0相同,并且从文件的第一行推断出列名;如果显式传递列名,则该行为与header = None相同。 。显式传递header = 0以便能够替换现有名称。标头可以是整数列表,这些整数指定列中多个索引的行位置,例如[0,1,3]。未指定的中间行将被跳过(例如,本示例中的2被跳过)。请注意,如果skip_blank_lines = True,则此参数将忽略注释行和空行,因此header = 0表示数据的第一行,而不是文件的第一行。
名称:类似数组,默认为无
要使用的列名列表。如果文件不包含标题行,则应显式传递header = None。此列表中的重复项将导致发出用户警告。”