負載CSV成2D矩陣與numpy的用於繪圖

鑑於這種CSV文件：負載CSV成2D矩陣與numpy的用於繪圖

"A","B","C","D","E","F","timestamp" 
611.88243,9089.5601,5133.0,864.07514,1715.37476,765.22777,1.291111964948E12 
611.88243,9089.5601,5133.0,864.07514,1715.37476,765.22777,1.291113113366E12 
611.88243,9089.5601,5133.0,864.07514,1715.37476,765.22777,1.291120650486E12

我只是想將其加載爲矩陣/ ndarray與3行7列。然而，出於某種原因，我可以擺脫numpy的是一個3行（每行一個）和沒有列的ndarray。

r = np.genfromtxt(fname,delimiter=',',dtype=None, names=True) 
print r 
print r.shape 

[ (611.88243, 9089.5601000000006, 5133.0, 864.07514000000003, 1715.3747599999999, 765.22776999999996, 1291111964948.0) 
(611.88243, 9089.5601000000006, 5133.0, 864.07514000000003, 1715.3747599999999, 765.22776999999996, 1291113113366.0) 
(611.88243, 9089.5601000000006, 5133.0, 864.07514000000003, 1715.3747599999999, 765.22776999999996, 1291120650486.0)] 
(3,)

我可以手動迭代並將其轉換成我想要的形狀，但這看起來很愚蠢。我只是想加載它作爲一個適當的矩陣，所以我可以在不同的維度切片並繪製它，就像在matlab中一樣。

來源

2010-11-30 dgorissen

109

純numpy的

numpy.loadtxt(open("test.csv", "rb"), delimiter=",", skiprows=1)

退房的loadtxt文檔。

您也可以使用Python的CSV模塊：

import csv 
import numpy 
reader = csv.reader(open("test.csv", "rb"), delimiter=",") 
x = list(reader) 
result = numpy.array(x).astype("float")

你將不得不將它轉化成自己喜歡的數字類型。我想你可以寫了整個事情在同一行：

 
result = numpy.array(list(csv.reader(open("test.csv", "rb"), delimiter=","))).astype("float")

新增提示：

你也可以使用pandas.io.parsers.read_csv並得到相關numpy陣列可以更快。

來源

2010-11-30 16:20:18

我認爲使用dtype哪裏有一個名稱行混淆了例程。嘗試

>>> r = np.genfromtxt(fname, delimiter=',', names=True) 
>>> r 
array([[ 6.11882430e+02, 9.08956010e+03, 5.13300000e+03, 
      8.64075140e+02, 1.71537476e+03, 7.65227770e+02, 
      1.29111196e+12], 
     [ 6.11882430e+02, 9.08956010e+03, 5.13300000e+03, 
      8.64075140e+02, 1.71537476e+03, 7.65227770e+02, 
      1.29111311e+12], 
     [ 6.11882430e+02, 9.08956010e+03, 5.13300000e+03, 
      8.64075140e+02, 1.71537476e+03, 7.65227770e+02, 
      1.29112065e+12]]) 
>>> r[:,0] # Slice 0'th column 
array([ 611.88243, 611.88243, 611.88243])

來源

2010-11-30 16:07:09 mtrw

有趣的是，這並不在我的情況發生變化的結果。我使用的Python 2.5和numpy 1.4.1所以也許這就是問題 – dgorissen 2010-11-30 16:55:36

我使用Python 2.6和NumPy 1.3.0！我更喜歡舊的行爲。 – mtrw 2010-11-30 17:14:53

您可以將帶有標題的CSV文件讀取到NumPy record array與np.recfromcsv。例如：

import numpy as np 
import StringIO 

csv_text = """\ 
"A","B","C","D","E","F","timestamp" 
611.88243,9089.5601,5133.0,864.07514,1715.37476,765.22777,1.291111964948E12 
611.88243,9089.5601,5133.0,864.07514,1715.37476,765.22777,1.291113113366E12 
611.88243,9089.5601,5133.0,864.07514,1715.37476,765.22777,1.291120650486E12 
""" 
# Make a file-like object 
csv_file = StringIO.StringIO(csv_text) 
csv_file.seek(0) 

# Read the CSV file into a Numpy record array 
r = np.recfromcsv(csv_file, case_sensitive=True) 
print(repr(r))

，看起來像這樣：

rec.array([ (611.88243, 9089.5601, 5133., 864.07514, 1715.37476, 765.22777, 1.29111196e+12), 
      (611.88243, 9089.5601, 5133., 864.07514, 1715.37476, 765.22777, 1.29111311e+12), 
      (611.88243, 9089.5601, 5133., 864.07514, 1715.37476, 765.22777, 1.29112065e+12)], 
      dtype=[('A', '<f8'), ('B', '<f8'), ('C', '<f8'), ('D', '<f8'), ('E', '<f8'), ('F', '<f8'), ('timestamp', '<f8')])

你可以這樣r['E']訪問一個名爲列：

array([ 1715.37476, 1715.37476, 1715.37476])

來源

2016-02-22 03:04:44

負載CSV成2D矩陣與numpy的用於繪圖

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