Python Pandas Pivot圖像數據表

Question

我有一個正在使用的Pandas數據框，我創建了一個3000000x3（像素x搶帶）的表，現在正嘗試對其進行透視，所以我有了一個3x3000000的表，然后對新數據運行PCA。

我正在使用該Pandas Pivot函數，但無法弄清楚我在做什么錯。

import pandas as pd 
import numpy as np 
import random as rd
from sklearn.decomposition import PCA
from sklearn import preprocessing
import matplotlib.pyplot as plt
import cv2 

#read in image
img = cv2.imread('/Volumes/EXTERNAL/Stitched-Photos-for-Chris/p7_0015_20161005-949am-75m-pass-1.jpg.png',1)
row,col = img.shape[:2]
#print(row , col)

#get a unique pixel ID for each pixel
pixel = [i for i in range(0,row*col)]
data = pd.DataFrame(columns=['bBand','gBand','rBand'],index = pixel)

#populate data for each band
b,g,r = cv2.split(img)
data.loc[pixel,'bBand'] = b.flat[:]
data.loc[pixel,'gBand'] = g.flat[:]
data.loc[pixel,'rBand'] = r.flat[:]

datapivoted = data.pivot(index=['bBand','gBand','rBand'], columns=pixel, values=[data.loc[pixel,'bBand'],data.loc[pixel,'bBand'],data.loc[pixel,'bBand']])

print(data.head())
print(data.shape)

更新

使用以下代碼重新創建數據框，我認為這是正確的並且更有效，但仍然無法解決

img = cv2.imread('/Volumes/EXTERNAL/Stitched-Photos-for-Chris/p7_0015_20161005-949am-75m-pass-1.jpg.png',1)
row,col = img.shape[:2]
#print(row , col)
b,g,r = cv2.split(img)

data = pd.DataFrame({'bBnad':b.flat[:],'gBnad':g.flat[:],'rBnad':r.flat[:]})

Answer 1

認真考慮了這個問題。 當我需要完全交換軸時，就像使用.T轉置一樣簡單

data = pd.DataFrame({'bBnad':b.flat[:],'gBnad':g.flat[:],'rBnad':r.flat[:]})
datapivoted = data.T
print(datapivoted.head())
print(datapivoted.shape)