小编nic*_*cap的帖子

我已经生成了一些加速度计数据的以下 3D 散点图：

这是非常基本的，但我对它的外观感到满意，因为这是我第一次尝试使用 Python。这是我编写的用于进行此可视化的代码：

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib
matplotlib.style.use('ggplot')
from mpl_toolkits.mplot3d import Axes3D
from mpldatacursor import datacursor

AccX = pd.read_csv('Data_Retrieval_April_05_2017.csv')
AccX.columns = ['Tag', 'Timestamp', 'X']
AccX = AccX[AccX['Tag'].str.contains("ACC856:AccelerationX")]
del AccX['Tag']

print(AccX.head())

AccY = pd.read_csv('Data_Retrieval_April_05_2017.csv')
AccY.columns = ['Tag', 'Timestamp', 'Y']
AccY = AccY[AccY['Tag'].str.contains("ACC856:AccelerationY")]
del AccY['Tag']

print(AccY.head())

AccZ = pd.read_csv('Data_Retrieval_April_05_2017.csv')
AccZ.columns = ['Tag', 'Timestamp', 'Z']
AccZ = AccZ[AccZ['Tag'].str.contains("ACC856:AccelerationZ")]
del AccZ['Tag']

print(AccZ.head())

Accel = AccX.merge(AccY,on='Timestamp').merge(AccZ,on='Timestamp')

Accel = Accel.set_index(['Timestamp'])

print(Accel.head())

Accel['X'] = Accel.X.astype(float)
Accel['Y'] = Accel.Y.astype(float)
Accel['Z'] …