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model_analysis/velocity_calculation.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Calculating Velocity From IMU"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Imports"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"from scipy.stats import stats\n",
"import matplotlib.pyplot as plt\n",
"from datetime import datetime"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Load the Data"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
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" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>2018-02-12 21:27:49.509790208</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>1970-01-01 00:08:11.719079000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>1970-01-01 00:08:11.739232000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>1970-01-01 00:08:11.760189000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>1970-01-01 00:08:11.780137000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>974</th>\n",
" <td>1970-01-01 00:08:30.864614000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>975</th>\n",
" <td>1970-01-01 00:08:30.885577000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>976</th>\n",
" <td>1970-01-01 00:08:30.905615000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>977</th>\n",
" <td>1970-01-01 00:08:30.926575000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>978</th>\n",
" <td>1970-01-01 00:08:30.946621999</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>979</th>\n",
" <td>1970-01-01 00:08:30.967586999</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>980</th>\n",
" <td>1970-01-01 00:08:30.988654999</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>27.0</td>\n",
" <td>988654999.0</td>\n",
" <td>510.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>981</th>\n",
" <td>1970-01-01 00:08:30.988547999</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>982</th>\n",
" <td>1970-01-01 00:08:31.008592000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>983</th>\n",
" <td>1970-01-01 00:08:31.028617999</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>984</th>\n",
" <td>1970-01-01 00:08:31.049590000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>985</th>\n",
" <td>1970-01-01 00:08:31.070549000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>986</th>\n",
" <td>1970-01-01 00:08:31.090603999</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>987</th>\n",
" <td>1970-01-01 00:08:31.111438000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>988</th>\n",
" <td>1970-01-01 00:08:31.131477000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>989</th>\n",
" <td>1970-01-01 00:08:31.152437000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>990</th>\n",
" <td>1970-01-01 00:08:31.172477000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>991</th>\n",
" <td>1970-01-01 00:08:31.193439000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>992</th>\n",
" <td>1970-01-01 00:08:31.213474000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>993</th>\n",
" <td>1970-01-01 00:08:31.234448999</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>994</th>\n",
" <td>1970-01-01 00:08:31.254484999</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>995</th>\n",
" <td>1970-01-01 00:08:31.275455000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>996</th>\n",
" <td>1970-01-01 00:08:31.296421000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>997</th>\n",
" <td>1970-01-01 00:08:31.316463999</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>998</th>\n",
" <td>1970-01-01 00:08:31.337421000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>999</th>\n",
" <td>1970-01-01 00:08:31.357461999</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1000</th>\n",
" <td>1970-01-01 00:08:31.378457000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1001</th>\n",
" <td>1970-01-01 00:08:31.398462999</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1002</th>\n",
" <td>1970-01-01 00:08:31.419309999</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1003</th>\n",
" <td>1970-01-01 00:08:31.439351999</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1004 rows × 71 columns</p>\n",
"</div>"
],
"text/plain": [
" Unnamed: 0 chatter__data \\\n",
"0 2018-02-12 21:27:49.271806208 NaN \n",
"1 2018-02-12 21:27:48.656828672 NaN \n",
"2 1970-01-01 00:08:11.411240000 NaN \n",
"3 2018-02-12 21:27:48.717360896 NaN \n",
"4 1970-01-01 00:08:11.431257000 NaN \n",
"5 1970-01-01 00:08:11.452209999 NaN \n",
"6 2018-02-12 21:27:48.890218496 NaN \n",
"7 2018-02-12 21:27:48.926719232 NaN \n",
"8 2018-02-12 21:27:48.965212672 NaN \n",
"9 1970-01-01 00:01:18.013442999 NaN \n",
"10 1970-01-01 00:02:53.354259000 NaN \n",
"11 2018-02-12 21:27:49.005249280 NaN \n",
"12 2018-02-12 21:27:49.066365440 NaN \n",
"13 1970-01-01 00:08:11.472264999 NaN \n",
"14 1970-01-01 00:08:11.493243000 NaN \n",
"15 1970-01-01 00:08:11.513268999 NaN \n",
"16 1970-01-01 00:08:11.534220000 NaN \n",
"17 1970-01-01 00:08:11.554260999 NaN \n",
"18 1970-01-01 00:08:11.575220000 NaN \n",
"19 1970-01-01 00:08:11.595257000 NaN \n",
"20 1970-01-01 00:08:11.616220999 NaN \n",
"21 1970-01-01 00:08:11.636254000 NaN \n",
"22 1970-01-01 00:08:11.657216000 NaN \n",
"23 1970-01-01 00:08:11.677258999 NaN \n",
"24 1970-01-01 00:08:11.698255000 NaN \n",
"25 2018-02-12 21:27:49.509790208 NaN \n",
"26 1970-01-01 00:08:11.719079000 NaN \n",
"27 1970-01-01 00:08:11.739232000 NaN \n",
"28 1970-01-01 00:08:11.760189000 NaN \n",
"29 1970-01-01 00:08:11.780137000 NaN \n",
"... ... ... \n",
"974 1970-01-01 00:08:30.864614000 NaN \n",
"975 1970-01-01 00:08:30.885577000 NaN \n",
"976 1970-01-01 00:08:30.905615000 NaN \n",
"977 1970-01-01 00:08:30.926575000 NaN \n",
"978 1970-01-01 00:08:30.946621999 NaN \n",
"979 1970-01-01 00:08:30.967586999 NaN \n",
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"981 1970-01-01 00:08:30.988547999 NaN \n",
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"983 1970-01-01 00:08:31.028617999 NaN \n",
"984 1970-01-01 00:08:31.049590000 NaN \n",
"985 1970-01-01 00:08:31.070549000 NaN \n",
"986 1970-01-01 00:08:31.090603999 NaN \n",
"987 1970-01-01 00:08:31.111438000 NaN \n",
"988 1970-01-01 00:08:31.131477000 NaN \n",
"989 1970-01-01 00:08:31.152437000 NaN \n",
"990 1970-01-01 00:08:31.172477000 NaN \n",
"991 1970-01-01 00:08:31.193439000 NaN \n",
"992 1970-01-01 00:08:31.213474000 NaN \n",
"993 1970-01-01 00:08:31.234448999 NaN \n",
"994 1970-01-01 00:08:31.254484999 NaN \n",
"995 1970-01-01 00:08:31.275455000 NaN \n",
"996 1970-01-01 00:08:31.296421000 NaN \n",
"997 1970-01-01 00:08:31.316463999 NaN \n",
"998 1970-01-01 00:08:31.337421000 NaN \n",
"999 1970-01-01 00:08:31.357461999 NaN \n",
"1000 1970-01-01 00:08:31.378457000 NaN \n",
"1001 1970-01-01 00:08:31.398462999 NaN \n",
"1002 1970-01-01 00:08:31.419309999 NaN \n",
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"\n",
" diagnostics__header_frame_id diagnostics__header_seq \\\n",
"0 NaN NaN \n",
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"27 NaN NaN \n",
"28 NaN NaN \n",
"29 NaN NaN \n",
"... ... ... \n",
"974 NaN NaN \n",
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"976 NaN NaN \n",
"977 NaN NaN \n",
"978 NaN NaN \n",
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"980 1.0 27.0 \n",
"981 NaN NaN \n",
"982 NaN NaN \n",
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"985 NaN NaN \n",
"986 NaN NaN \n",
"987 NaN NaN \n",
"988 NaN NaN \n",
"989 NaN NaN \n",
"990 NaN NaN \n",
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"995 NaN NaN \n",
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"998 NaN NaN \n",
"999 NaN NaN \n",
"1000 NaN NaN \n",
"1001 NaN NaN \n",
"1002 NaN NaN \n",
"1003 NaN NaN \n",
"\n",
" diagnostics__header_stamp_nsecs diagnostics__header_stamp_secs \\\n",
"0 NaN NaN \n",
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"20 NaN NaN \n",
"21 NaN NaN \n",
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"23 NaN NaN \n",
"24 NaN NaN \n",
"25 NaN NaN \n",
"26 NaN NaN \n",
"27 NaN NaN \n",
"28 NaN NaN \n",
"29 NaN NaN \n",
"... ... ... \n",
"974 NaN NaN \n",
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"976 NaN NaN \n",
"977 NaN NaN \n",
"978 NaN NaN \n",
"979 NaN NaN \n",
"980 988654999.0 510.0 \n",
"981 NaN NaN \n",
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"987 NaN NaN \n",
"988 NaN NaN \n",
"989 NaN NaN \n",
"990 NaN NaN \n",
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"993 NaN NaN \n",
"994 NaN NaN \n",
"995 NaN NaN \n",
"996 NaN NaN \n",
"997 NaN NaN \n",
"998 NaN NaN \n",
"999 NaN NaN \n",
"1000 NaN NaN \n",
"1001 NaN NaN \n",
"1002 NaN NaN \n",
"1003 NaN NaN \n",
"\n",
" drive_parameters__angle drive_parameters__velocity \\\n",
"0 NaN NaN \n",
"1 NaN NaN \n",
"2 NaN NaN \n",
"3 NaN NaN \n",
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"9 NaN NaN \n",
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"11 NaN NaN \n",
"12 NaN NaN \n",
"13 NaN NaN \n",
"14 NaN NaN \n",
"15 NaN NaN \n",
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"20 NaN NaN \n",
"21 NaN NaN \n",
"22 NaN NaN \n",
"23 NaN NaN \n",
"24 NaN NaN \n",
"25 NaN NaN \n",
"26 NaN NaN \n",
"27 NaN NaN \n",
"28 NaN NaN \n",
"29 NaN NaN \n",
"... ... ... \n",
"974 NaN NaN \n",
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"976 NaN NaN \n",
"977 NaN NaN \n",
"978 NaN NaN \n",
"979 NaN NaN \n",
"980 NaN NaN \n",
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"982 NaN NaN \n",
"983 NaN NaN \n",
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"985 NaN NaN \n",
"986 NaN NaN \n",
"987 NaN NaN \n",
"988 NaN NaN \n",
"989 NaN NaN \n",
"990 NaN NaN \n",
"991 NaN NaN \n",
"992 NaN NaN \n",
"993 NaN NaN \n",
"994 NaN NaN \n",
"995 NaN NaN \n",
"996 NaN NaN \n",
"997 NaN NaN \n",
"998 NaN NaN \n",
"999 NaN NaN \n",
"1000 NaN NaN \n",
"1001 NaN NaN \n",
"1002 NaN NaN \n",
"1003 NaN NaN \n",
"\n",
" drive_pwm__pwm_angle drive_pwm__pwm_drive ... \\\n",
"0 NaN NaN ... \n",
"1 NaN NaN ... \n",
"2 NaN NaN ... \n",
"3 NaN NaN ... \n",
"4 NaN NaN ... \n",
"5 NaN NaN ... \n",
"6 NaN NaN ... \n",
"7 NaN NaN ... \n",
"8 NaN NaN ... \n",
"9 NaN NaN ... \n",
"10 NaN NaN ... \n",
"11 NaN NaN ... \n",
"12 NaN NaN ... \n",
"13 NaN NaN ... \n",
"14 NaN NaN ... \n",
"15 NaN NaN ... \n",
"16 NaN NaN ... \n",
"17 NaN NaN ... \n",
"18 NaN NaN ... \n",
"19 NaN NaN ... \n",
"20 NaN NaN ... \n",
"21 NaN NaN ... \n",
"22 NaN NaN ... \n",
"23 NaN NaN ... \n",
"24 NaN NaN ... \n",
"25 NaN NaN ... \n",
"26 NaN NaN ... \n",
"27 NaN NaN ... \n",
"28 NaN NaN ... \n",
"29 NaN NaN ... \n",
"... ... ... ... \n",
"974 NaN NaN ... \n",
"975 NaN NaN ... \n",
"976 NaN NaN ... \n",
"977 NaN NaN ... \n",
"978 NaN NaN ... \n",
"979 NaN NaN ... \n",
"980 NaN NaN ... \n",
"981 NaN NaN ... \n",
"982 NaN NaN ... \n",
"983 NaN NaN ... \n",
"984 NaN NaN ... \n",
"985 NaN NaN ... \n",
"986 NaN NaN ... \n",
"987 NaN NaN ... \n",
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"989 NaN NaN ... \n",
"990 NaN NaN ... \n",
"991 NaN NaN ... \n",
"992 NaN NaN ... \n",
"993 NaN NaN ... \n",
"994 NaN NaN ... \n",
"995 NaN NaN ... \n",
"996 NaN NaN ... \n",
"997 NaN NaN ... \n",
"998 NaN NaN ... \n",
"999 NaN NaN ... \n",
"1000 NaN NaN ... \n",
"1001 NaN NaN ... \n",
"1002 NaN NaN ... \n",
"1003 NaN NaN ... \n",
"\n",
" rosout_agg__file rosout_agg__function rosout_agg__header_frame_id \\\n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"2 NaN NaN NaN \n",
"3 NaN NaN NaN \n",
"4 NaN NaN NaN \n",
"5 NaN NaN NaN \n",
"6 NaN NaN NaN \n",
"7 NaN NaN NaN \n",
"8 NaN NaN NaN \n",
"9 NaN NaN NaN \n",
"10 NaN NaN NaN \n",
"11 NaN NaN NaN \n",
"12 NaN NaN NaN \n",
"13 NaN NaN NaN \n",
"14 NaN NaN NaN \n",
"15 NaN NaN NaN \n",
"16 NaN NaN NaN \n",
"17 NaN NaN NaN \n",
"18 NaN NaN NaN \n",
"19 NaN NaN NaN \n",
"20 NaN NaN NaN \n",
"21 NaN NaN NaN \n",
"22 NaN NaN NaN \n",
"23 NaN NaN NaN \n",
"24 NaN NaN NaN \n",
"25 NaN NaN NaN \n",
"26 NaN NaN NaN \n",
"27 NaN NaN NaN \n",
"28 NaN NaN NaN \n",
"29 NaN NaN NaN \n",
"... ... ... ... \n",
"974 NaN NaN NaN \n",
"975 NaN NaN NaN \n",
"976 NaN NaN NaN \n",
"977 NaN NaN NaN \n",
"978 NaN NaN NaN \n",
"979 NaN NaN NaN \n",
"980 NaN NaN NaN \n",
"981 NaN NaN NaN \n",
"982 NaN NaN NaN \n",
"983 NaN NaN NaN \n",
"984 NaN NaN NaN \n",
"985 NaN NaN NaN \n",
"986 NaN NaN NaN \n",
"987 NaN NaN NaN \n",
"988 NaN NaN NaN \n",
"989 NaN NaN NaN \n",
"990 NaN NaN NaN \n",
"991 NaN NaN NaN \n",
"992 NaN NaN NaN \n",
"993 NaN NaN NaN \n",
"994 NaN NaN NaN \n",
"995 NaN NaN NaN \n",
"996 NaN NaN NaN \n",
"997 NaN NaN NaN \n",
"998 NaN NaN NaN \n",
"999 NaN NaN NaN \n",
"1000 NaN NaN NaN \n",
"1001 NaN NaN NaN \n",
"1002 NaN NaN NaN \n",
"1003 NaN NaN NaN \n",
"\n",
" rosout_agg__header_seq rosout_agg__header_stamp_nsecs \\\n",
"0 NaN NaN \n",
"1 NaN NaN \n",
"2 NaN NaN \n",
"3 NaN NaN \n",
"4 NaN NaN \n",
"5 NaN NaN \n",
"6 NaN NaN \n",
"7 NaN NaN \n",
"8 NaN NaN \n",
"9 NaN NaN \n",
"10 NaN NaN \n",
"11 NaN NaN \n",
"12 NaN NaN \n",
"13 NaN NaN \n",
"14 NaN NaN \n",
"15 NaN NaN \n",
"16 NaN NaN \n",
"17 NaN NaN \n",
"18 NaN NaN \n",
"19 NaN NaN \n",
"20 NaN NaN \n",
"21 NaN NaN \n",
"22 NaN NaN \n",
"23 NaN NaN \n",
"24 NaN NaN \n",
"25 NaN NaN \n",
"26 NaN NaN \n",
"27 NaN NaN \n",
"28 NaN NaN \n",
"29 NaN NaN \n",
"... ... ... \n",
"974 NaN NaN \n",
"975 NaN NaN \n",
"976 NaN NaN \n",
"977 NaN NaN \n",
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"982 NaN NaN \n",
"983 NaN NaN \n",
"984 NaN NaN \n",
"985 NaN NaN \n",
"986 NaN NaN \n",
"987 NaN NaN \n",
"988 NaN NaN \n",
"989 NaN NaN \n",
"990 NaN NaN \n",
"991 NaN NaN \n",
"992 NaN NaN \n",
"993 NaN NaN \n",
"994 NaN NaN \n",
"995 NaN NaN \n",
"996 NaN NaN \n",
"997 NaN NaN \n",
"998 NaN NaN \n",
"999 NaN NaN \n",
"1000 NaN NaN \n",
"1001 NaN NaN \n",
"1002 NaN NaN \n",
"1003 NaN NaN \n",
"\n",
" rosout_agg__header_stamp_secs rosout_agg__level rosout_agg__line \\\n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"2 NaN NaN NaN \n",
"3 NaN NaN NaN \n",
"4 NaN NaN NaN \n",
"5 NaN NaN NaN \n",
"6 NaN NaN NaN \n",
"7 NaN NaN NaN \n",
"8 NaN NaN NaN \n",
"9 NaN NaN NaN \n",
"10 NaN NaN NaN \n",
"11 NaN NaN NaN \n",
"12 NaN NaN NaN \n",
"13 NaN NaN NaN \n",
"14 NaN NaN NaN \n",
"15 NaN NaN NaN \n",
"16 NaN NaN NaN \n",
"17 NaN NaN NaN \n",
"18 NaN NaN NaN \n",
"19 NaN NaN NaN \n",
"20 NaN NaN NaN \n",
"21 NaN NaN NaN \n",
"22 NaN NaN NaN \n",
"23 NaN NaN NaN \n",
"24 NaN NaN NaN \n",
"25 NaN NaN NaN \n",
"26 NaN NaN NaN \n",
"27 NaN NaN NaN \n",
"28 NaN NaN NaN \n",
"29 NaN NaN NaN \n",
"... ... ... ... \n",
"974 NaN NaN NaN \n",
"975 NaN NaN NaN \n",
"976 NaN NaN NaN \n",
"977 NaN NaN NaN \n",
"978 NaN NaN NaN \n",
"979 NaN NaN NaN \n",
"980 NaN NaN NaN \n",
"981 NaN NaN NaN \n",
"982 NaN NaN NaN \n",
"983 NaN NaN NaN \n",
"984 NaN NaN NaN \n",
"985 NaN NaN NaN \n",
"986 NaN NaN NaN \n",
"987 NaN NaN NaN \n",
"988 NaN NaN NaN \n",
"989 NaN NaN NaN \n",
"990 NaN NaN NaN \n",
"991 NaN NaN NaN \n",
"992 NaN NaN NaN \n",
"993 NaN NaN NaN \n",
"994 NaN NaN NaN \n",
"995 NaN NaN NaN \n",
"996 NaN NaN NaN \n",
"997 NaN NaN NaN \n",
"998 NaN NaN NaN \n",
"999 NaN NaN NaN \n",
"1000 NaN NaN NaN \n",
"1001 NaN NaN NaN \n",
"1002 NaN NaN NaN \n",
"1003 NaN NaN NaN \n",
"\n",
" rosout_agg__msg rosout_agg__name \n",
"0 NaN NaN \n",
"1 NaN NaN \n",
"2 NaN NaN \n",
"3 NaN NaN \n",
"4 NaN NaN \n",
"5 NaN NaN \n",
"6 NaN NaN \n",
"7 NaN NaN \n",
"8 NaN NaN \n",
"9 NaN NaN \n",
"10 NaN NaN \n",
"11 NaN NaN \n",
"12 NaN NaN \n",
"13 NaN NaN \n",
"14 NaN NaN \n",
"15 NaN NaN \n",
"16 NaN NaN \n",
"17 NaN NaN \n",
"18 NaN NaN \n",
"19 NaN NaN \n",
"20 NaN NaN \n",
"21 NaN NaN \n",
"22 NaN NaN \n",
"23 NaN NaN \n",
"24 NaN NaN \n",
"25 NaN NaN \n",
"26 NaN NaN \n",
"27 NaN NaN \n",
"28 NaN NaN \n",
"29 NaN NaN \n",
"... ... ... \n",
"974 NaN NaN \n",
"975 NaN NaN \n",
"976 NaN NaN \n",
"977 NaN NaN \n",
"978 NaN NaN \n",
"979 NaN NaN \n",
"980 NaN NaN \n",
"981 NaN NaN \n",
"982 NaN NaN \n",
"983 NaN NaN \n",
"984 NaN NaN \n",
"985 NaN NaN \n",
"986 NaN NaN \n",
"987 NaN NaN \n",
"988 NaN NaN \n",
"989 NaN NaN \n",
"990 NaN NaN \n",
"991 NaN NaN \n",
"992 NaN NaN \n",
"993 NaN NaN \n",
"994 NaN NaN \n",
"995 NaN NaN \n",
"996 NaN NaN \n",
"997 NaN NaN \n",
"998 NaN NaN \n",
"999 NaN NaN \n",
"1000 NaN NaN \n",
"1001 NaN NaN \n",
"1002 NaN NaN \n",
"1003 NaN NaN \n",
"\n",
"[1004 rows x 71 columns]"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Load the Data\n",
"base_path = './data/Round3/'\n",
"bag = pd.read_csv(base_path + 'Test1_2018-02-12-16-27-48.csv')\n",
"\n",
"# Data Preview\n",
"bag"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(['Unnamed: 0', 'chatter__data', 'diagnostics__header_frame_id',\n",
" 'diagnostics__header_seq', 'diagnostics__header_stamp_nsecs',\n",
" 'diagnostics__header_stamp_secs', 'drive_parameters__angle',\n",
" 'drive_parameters__velocity', 'drive_pwm__pwm_angle',\n",
" 'drive_pwm__pwm_drive', 'imu__angular_velocity_covariance0',\n",
" 'imu__angular_velocity_covariance1',\n",
" 'imu__angular_velocity_covariance2',\n",
" 'imu__angular_velocity_covariance3',\n",
" 'imu__angular_velocity_covariance4',\n",
" 'imu__angular_velocity_covariance5',\n",
" 'imu__angular_velocity_covariance6',\n",
" 'imu__angular_velocity_covariance7',\n",
" 'imu__angular_velocity_covariance8', 'imu__angular_velocity_x',\n",
" 'imu__angular_velocity_y', 'imu__angular_velocity_z',\n",
" 'imu__header_frame_id', 'imu__header_seq',\n",
" 'imu__header_stamp_nsecs', 'imu__header_stamp_secs',\n",
" 'imu__linear_acceleration_covariance0',\n",
" 'imu__linear_acceleration_covariance1',\n",
" 'imu__linear_acceleration_covariance2',\n",
" 'imu__linear_acceleration_covariance3',\n",
" 'imu__linear_acceleration_covariance4',\n",
" 'imu__linear_acceleration_covariance5',\n",
" 'imu__linear_acceleration_covariance6',\n",
" 'imu__linear_acceleration_covariance7',\n",
" 'imu__linear_acceleration_covariance8',\n",
" 'imu__linear_acceleration_x', 'imu__linear_acceleration_y',\n",
" 'imu__linear_acceleration_z', 'imu__orientation_covariance0',\n",
" 'imu__orientation_covariance1', 'imu__orientation_covariance2',\n",
" 'imu__orientation_covariance3', 'imu__orientation_covariance4',\n",
" 'imu__orientation_covariance5', 'imu__orientation_covariance6',\n",
" 'imu__orientation_covariance7', 'imu__orientation_covariance8',\n",
" 'imu__orientation_w', 'imu__orientation_x', 'imu__orientation_y',\n",
" 'imu__orientation_z', 'rosout__file', 'rosout__function',\n",
" 'rosout__header_frame_id', 'rosout__header_seq',\n",
" 'rosout__header_stamp_nsecs', 'rosout__header_stamp_secs',\n",
" 'rosout__level', 'rosout__line', 'rosout__msg', 'rosout__name',\n",
" 'rosout_agg__file', 'rosout_agg__function',\n",
" 'rosout_agg__header_frame_id', 'rosout_agg__header_seq',\n",
" 'rosout_agg__header_stamp_nsecs', 'rosout_agg__header_stamp_secs',\n",
" 'rosout_agg__level', 'rosout_agg__line', 'rosout_agg__msg',\n",
" 'rosout_agg__name'], dtype=object)"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bag.columns.values"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
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" <td>NaN</td>\n",
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" <tr>\n",
" <th>10</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <th>11</th>\n",
" <td>NaN</td>\n",
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" <th>12</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <tr>\n",
" <th>13</th>\n",
" <td>183.0</td>\n",
" <td>491.0</td>\n",
" <td>472264999.0</td>\n",
" <td>0.157049</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>184.0</td>\n",
" <td>491.0</td>\n",
" <td>493243000.0</td>\n",
" <td>0.235191</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>185.0</td>\n",
" <td>491.0</td>\n",
" <td>513268999.0</td>\n",
" <td>0.235191</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>186.0</td>\n",
" <td>491.0</td>\n",
" <td>534220000.0</td>\n",
" <td>0.117595</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>187.0</td>\n",
" <td>491.0</td>\n",
" <td>554260999.0</td>\n",
" <td>0.117595</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>188.0</td>\n",
" <td>491.0</td>\n",
" <td>575220000.0</td>\n",
" <td>0.196120</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>189.0</td>\n",
" <td>491.0</td>\n",
" <td>595257000.0</td>\n",
" <td>0.235191</td>\n",
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" <tr>\n",
" <th>20</th>\n",
" <td>190.0</td>\n",
" <td>491.0</td>\n",
" <td>616220999.0</td>\n",
" <td>0.117595</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>191.0</td>\n",
" <td>491.0</td>\n",
" <td>636254000.0</td>\n",
" <td>0.117595</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>192.0</td>\n",
" <td>491.0</td>\n",
" <td>657216000.0</td>\n",
" <td>0.117595</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>193.0</td>\n",
" <td>491.0</td>\n",
" <td>677258999.0</td>\n",
" <td>0.157049</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>194.0</td>\n",
" <td>491.0</td>\n",
" <td>698255000.0</td>\n",
" <td>0.157049</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <tr>\n",
" <th>26</th>\n",
" <td>195.0</td>\n",
" <td>491.0</td>\n",
" <td>719079000.0</td>\n",
" <td>0.196120</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>196.0</td>\n",
" <td>491.0</td>\n",
" <td>739232000.0</td>\n",
" <td>0.157049</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>197.0</td>\n",
" <td>491.0</td>\n",
" <td>760189000.0</td>\n",
" <td>0.157049</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>198.0</td>\n",
" <td>491.0</td>\n",
" <td>780137000.0</td>\n",
" <td>0.196120</td>\n",
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" <tr>\n",
" <th>975</th>\n",
" <td>1129.0</td>\n",
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" <td>0.117595</td>\n",
" </tr>\n",
" <tr>\n",
" <th>976</th>\n",
" <td>1130.0</td>\n",
" <td>510.0</td>\n",
" <td>905615000.0</td>\n",
" <td>0.078525</td>\n",
" </tr>\n",
" <tr>\n",
" <th>977</th>\n",
" <td>1131.0</td>\n",
" <td>510.0</td>\n",
" <td>926575000.0</td>\n",
" <td>0.039071</td>\n",
" </tr>\n",
" <tr>\n",
" <th>978</th>\n",
" <td>1132.0</td>\n",
" <td>510.0</td>\n",
" <td>946621999.0</td>\n",
" <td>0.078525</td>\n",
" </tr>\n",
" <tr>\n",
" <th>979</th>\n",
" <td>1133.0</td>\n",
" <td>510.0</td>\n",
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" <td>0.117595</td>\n",
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" <tr>\n",
" <th>980</th>\n",
" <td>NaN</td>\n",
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" <tr>\n",
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" <th>982</th>\n",
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" <tr>\n",
" <th>983</th>\n",
" <td>1136.0</td>\n",
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" <td>-0.000000</td>\n",
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" <tr>\n",
" <th>984</th>\n",
" <td>1137.0</td>\n",
" <td>511.0</td>\n",
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" <td>0.039071</td>\n",
" </tr>\n",
" <tr>\n",
" <th>985</th>\n",
" <td>1138.0</td>\n",
" <td>511.0</td>\n",
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" <td>0.157049</td>\n",
" </tr>\n",
" <tr>\n",
" <th>986</th>\n",
" <td>1139.0</td>\n",
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" <td>0.117595</td>\n",
" </tr>\n",
" <tr>\n",
" <th>987</th>\n",
" <td>1140.0</td>\n",
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" <td>111438000.0</td>\n",
" <td>0.078525</td>\n",
" </tr>\n",
" <tr>\n",
" <th>988</th>\n",
" <td>1141.0</td>\n",
" <td>511.0</td>\n",
" <td>131477000.0</td>\n",
" <td>0.078525</td>\n",
" </tr>\n",
" <tr>\n",
" <th>989</th>\n",
" <td>1142.0</td>\n",
" <td>511.0</td>\n",
" <td>152437000.0</td>\n",
" <td>0.039071</td>\n",
" </tr>\n",
" <tr>\n",
" <th>990</th>\n",
" <td>1143.0</td>\n",
" <td>511.0</td>\n",
" <td>172477000.0</td>\n",
" <td>0.117595</td>\n",
" </tr>\n",
" <tr>\n",
" <th>991</th>\n",
" <td>1144.0</td>\n",
" <td>511.0</td>\n",
" <td>193439000.0</td>\n",
" <td>0.117595</td>\n",
" </tr>\n",
" <tr>\n",
" <th>992</th>\n",
" <td>1145.0</td>\n",
" <td>511.0</td>\n",
" <td>213474000.0</td>\n",
" <td>0.117595</td>\n",
" </tr>\n",
" <tr>\n",
" <th>993</th>\n",
" <td>1146.0</td>\n",
" <td>511.0</td>\n",
" <td>234448999.0</td>\n",
" <td>0.039071</td>\n",
" </tr>\n",
" <tr>\n",
" <th>994</th>\n",
" <td>1147.0</td>\n",
" <td>511.0</td>\n",
" <td>254484999.0</td>\n",
" <td>0.078525</td>\n",
" </tr>\n",
" <tr>\n",
" <th>995</th>\n",
" <td>1148.0</td>\n",
" <td>511.0</td>\n",
" <td>275455000.0</td>\n",
" <td>0.117595</td>\n",
" </tr>\n",
" <tr>\n",
" <th>996</th>\n",
" <td>1149.0</td>\n",
" <td>511.0</td>\n",
" <td>296421000.0</td>\n",
" <td>0.117595</td>\n",
" </tr>\n",
" <tr>\n",
" <th>997</th>\n",
" <td>1150.0</td>\n",
" <td>511.0</td>\n",
" <td>316463999.0</td>\n",
" <td>0.078525</td>\n",
" </tr>\n",
" <tr>\n",
" <th>998</th>\n",
" <td>1151.0</td>\n",
" <td>511.0</td>\n",
" <td>337421000.0</td>\n",
" <td>0.039071</td>\n",
" </tr>\n",
" <tr>\n",
" <th>999</th>\n",
" <td>1152.0</td>\n",
" <td>511.0</td>\n",
" <td>357461999.0</td>\n",
" <td>0.078525</td>\n",
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" <tr>\n",
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" <td>1153.0</td>\n",
" <td>511.0</td>\n",
" <td>378457000.0</td>\n",
" <td>0.117595</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1001</th>\n",
" <td>1154.0</td>\n",
" <td>511.0</td>\n",
" <td>398462999.0</td>\n",
" <td>0.039071</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1002</th>\n",
" <td>1155.0</td>\n",
" <td>511.0</td>\n",
" <td>419309999.0</td>\n",
" <td>0.039071</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1003</th>\n",
" <td>1156.0</td>\n",
" <td>511.0</td>\n",
" <td>439351999.0</td>\n",
" <td>0.078525</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1004 rows × 4 columns</p>\n",
"</div>"
],
"text/plain": [
" imu__header_seq imu__header_stamp_secs imu__header_stamp_nsecs \\\n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"2 180.0 491.0 411240000.0 \n",
"3 NaN NaN NaN \n",
"4 181.0 491.0 431257000.0 \n",
"5 182.0 491.0 452209999.0 \n",
"6 NaN NaN NaN \n",
"7 NaN NaN NaN \n",
"8 NaN NaN NaN \n",
"9 NaN NaN NaN \n",
"10 NaN NaN NaN \n",
"11 NaN NaN NaN \n",
"12 NaN NaN NaN \n",
"13 183.0 491.0 472264999.0 \n",
"14 184.0 491.0 493243000.0 \n",
"15 185.0 491.0 513268999.0 \n",
"16 186.0 491.0 534220000.0 \n",
"17 187.0 491.0 554260999.0 \n",
"18 188.0 491.0 575220000.0 \n",
"19 189.0 491.0 595257000.0 \n",
"20 190.0 491.0 616220999.0 \n",
"21 191.0 491.0 636254000.0 \n",
"22 192.0 491.0 657216000.0 \n",
"23 193.0 491.0 677258999.0 \n",
"24 194.0 491.0 698255000.0 \n",
"25 NaN NaN NaN \n",
"26 195.0 491.0 719079000.0 \n",
"27 196.0 491.0 739232000.0 \n",
"28 197.0 491.0 760189000.0 \n",
"29 198.0 491.0 780137000.0 \n",
"... ... ... ... \n",
"974 1128.0 510.0 864614000.0 \n",
"975 1129.0 510.0 885577000.0 \n",
"976 1130.0 510.0 905615000.0 \n",
"977 1131.0 510.0 926575000.0 \n",
"978 1132.0 510.0 946621999.0 \n",
"979 1133.0 510.0 967586999.0 \n",
"980 NaN NaN NaN \n",
"981 1134.0 510.0 988547999.0 \n",
"982 1135.0 511.0 8592000.0 \n",
"983 1136.0 511.0 28617999.0 \n",
"984 1137.0 511.0 49590000.0 \n",
"985 1138.0 511.0 70549000.0 \n",
"986 1139.0 511.0 90603999.0 \n",
"987 1140.0 511.0 111438000.0 \n",
"988 1141.0 511.0 131477000.0 \n",
"989 1142.0 511.0 152437000.0 \n",
"990 1143.0 511.0 172477000.0 \n",
"991 1144.0 511.0 193439000.0 \n",
"992 1145.0 511.0 213474000.0 \n",
"993 1146.0 511.0 234448999.0 \n",
"994 1147.0 511.0 254484999.0 \n",
"995 1148.0 511.0 275455000.0 \n",
"996 1149.0 511.0 296421000.0 \n",
"997 1150.0 511.0 316463999.0 \n",
"998 1151.0 511.0 337421000.0 \n",
"999 1152.0 511.0 357461999.0 \n",
"1000 1153.0 511.0 378457000.0 \n",
"1001 1154.0 511.0 398462999.0 \n",
"1002 1155.0 511.0 419309999.0 \n",
"1003 1156.0 511.0 439351999.0 \n",
"\n",
" imu__linear_acceleration_x \n",
"0 NaN \n",
"1 NaN \n",
"2 0.235191 \n",
"3 NaN \n",
"4 0.078525 \n",
"5 0.078525 \n",
"6 NaN \n",
"7 NaN \n",
"8 NaN \n",
"9 NaN \n",
"10 NaN \n",
"11 NaN \n",
"12 NaN \n",
"13 0.157049 \n",
"14 0.235191 \n",
"15 0.235191 \n",
"16 0.117595 \n",
"17 0.117595 \n",
"18 0.196120 \n",
"19 0.235191 \n",
"20 0.117595 \n",
"21 0.117595 \n",
"22 0.117595 \n",
"23 0.157049 \n",
"24 0.157049 \n",
"25 NaN \n",
"26 0.196120 \n",
"27 0.157049 \n",
"28 0.157049 \n",
"29 0.196120 \n",
"... ... \n",
"974 0.078525 \n",
"975 0.117595 \n",
"976 0.078525 \n",
"977 0.039071 \n",
"978 0.078525 \n",
"979 0.117595 \n",
"980 NaN \n",
"981 0.117595 \n",
"982 0.078525 \n",
"983 -0.000000 \n",
"984 0.039071 \n",
"985 0.157049 \n",
"986 0.117595 \n",
"987 0.078525 \n",
"988 0.078525 \n",
"989 0.039071 \n",
"990 0.117595 \n",
"991 0.117595 \n",
"992 0.117595 \n",
"993 0.039071 \n",
"994 0.078525 \n",
"995 0.117595 \n",
"996 0.117595 \n",
"997 0.078525 \n",
"998 0.039071 \n",
"999 0.078525 \n",
"1000 0.117595 \n",
"1001 0.039071 \n",
"1002 0.039071 \n",
"1003 0.078525 \n",
"\n",
"[1004 rows x 4 columns]"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# extract the particular data of interest\n",
"imu = bag.loc[:, ['imu__header_seq',\n",
" 'imu__header_stamp_secs',\n",
" 'imu__header_stamp_nsecs',\n",
" 'imu__linear_acceleration_x']]\n",
"imu"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>imu__header_seq</th>\n",
" <th>imu__header_stamp_secs</th>\n",
" <th>imu__header_stamp_nsecs</th>\n",
" <th>imu__linear_acceleration_x</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>180.0</td>\n",
" <td>491.0</td>\n",
" <td>411240000.0</td>\n",
" <td>0.235191</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>181.0</td>\n",
" <td>491.0</td>\n",
" <td>431257000.0</td>\n",
" <td>0.078525</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>182.0</td>\n",
" <td>491.0</td>\n",
" <td>452209999.0</td>\n",
" <td>0.078525</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>183.0</td>\n",
" <td>491.0</td>\n",
" <td>472264999.0</td>\n",
" <td>0.157049</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>184.0</td>\n",
" <td>491.0</td>\n",
" <td>493243000.0</td>\n",
" <td>0.235191</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" imu__header_seq imu__header_stamp_secs imu__header_stamp_nsecs \\\n",
"0 180.0 491.0 411240000.0 \n",
"1 181.0 491.0 431257000.0 \n",
"2 182.0 491.0 452209999.0 \n",
"3 183.0 491.0 472264999.0 \n",
"4 184.0 491.0 493243000.0 \n",
"\n",
" imu__linear_acceleration_x \n",
"0 0.235191 \n",
"1 0.078525 \n",
"2 0.078525 \n",
"3 0.157049 \n",
"4 0.235191 "
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"imu.dropna(how='any', subset=['imu__header_seq',\n",
" 'imu__header_stamp_secs',\n",
" 'imu__header_stamp_nsecs',\n",
" 'imu__linear_acceleration_x'], inplace=True)\n",
"imu.sort_values(by='imu__header_seq', inplace=True)\n",
"imu.reset_index(drop=True, inplace=True)\n",
"imu.head()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"imu.to_csv(base_path + 'Test1_2018-02-12-16-27-48_x_accel.csv')"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0 491411.240000\n",
"1 491431.257000\n",
"2 491452.209999\n",
"3 491472.264999\n",
"4 491493.243000\n",
"dtype: float64\n",
"959 511357.461999\n",
"960 511378.457000\n",
"961 511398.462999\n",
"962 511419.309999\n",
"963 511439.351999\n",
"dtype: float64\n"
]
}
],
"source": [
"time = imu.loc[:, 'imu__header_stamp_secs'] * 10**3 + imu.loc[:, 'imu__header_stamp_nsecs'] / 10**6\n",
"print(time.head())\n",
"print(time.tail())"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"0 491431.257000\n",
"1 491452.209999\n",
"2 491472.264999\n",
"3 491493.243000\n",
"4 491513.268999\n",
"dtype: float64"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"time_next = time.drop(time.index[0])\n",
"time_next.reset_index(drop=True, inplace=True)\n",
"time_next.head()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"958 511337.421000\n",
"959 511357.461999\n",
"960 511378.457000\n",
"961 511398.462999\n",
"962 511419.309999\n",
"dtype: float64"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"time_current = time.drop(time.index[-1])\n",
"time_current.reset_index(drop=True, inplace=True)\n",
"time_current.tail()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0 20.017000\n",
"1 20.952999\n",
"2 20.055000\n",
"3 20.978001\n",
"4 20.025999\n",
"dtype: float64\n",
"958 20.040999\n",
"959 20.995001\n",
"960 20.005999\n",
"961 20.847000\n",
"962 20.042000\n",
"dtype: float64\n"
]
}
],
"source": [
"time_delta = time_next - time_current\n",
"print(time_delta.head())\n",
"print(time_delta.tail())"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.16082223046875\n",
"0 -0.082298\n",
"1 -0.082298\n",
"2 -0.003773\n",
"3 0.074369\n",
"4 0.074369\n",
"Name: imu__linear_acceleration_x, dtype: float64\n",
"958 -0.082298\n",
"959 -0.043227\n",
"960 -0.121751\n",
"961 -0.121751\n",
"962 -0.082298\n",
"Name: imu__linear_acceleration_x, dtype: float64\n"
]
}
],
"source": [
"accel = imu.loc[1:, 'imu__linear_acceleration_x'] # discard the first row\n",
"accel.reset_index(drop=True, inplace=True)\n",
"\n",
"# Calculate gravity for each axis\n",
"first_couple_accel = accel.iloc[0:20]\n",
"means = np.mean(first_couple_accel)\n",
"print(means)\n",
"\n",
"accel = accel - means\n",
"print(accel.head())\n",
"print(accel.tail())"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0 -1.647351\n",
"1 -0.901719\n",
"2 0.707897\n",
"3 1.560104\n",
"4 0.311822\n",
"dtype: float64\n",
"958 -1.257818\n",
"959 -1.731860\n",
"960 -2.435759\n",
"961 -2.126905\n",
"962 NaN\n",
"dtype: float64\n"
]
}
],
"source": [
"accel_next = accel.drop(accel.index[0])\n",
"accel_next.reset_index(drop=True, inplace=True)\n",
"accel_current = accel.drop(accel.index[-1])\n",
"accel_current.reset_index(drop=True, inplace=True)\n",
"\n",
"summand = ((accel_next + accel_current)/2) * time_delta\n",
"print(summand.head())\n",
"print(summand.tail())"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0 -1.647351\n",
"1 -2.549070\n",
"2 -1.841174\n",
"3 -0.281070\n",
"4 0.030752\n",
"dtype: float64\n",
"958 746.289844\n",
"959 744.557985\n",
"960 742.122225\n",
"961 739.995320\n",
"962 NaN\n",
"dtype: float64\n"
]
}
],
"source": [
"growing_sums = pd.Series(np.zeros(summand.shape))\n",
"for indx, prod in enumerate(summand):\n",
" growing_sums.iat[indx] = growing_sums.iloc[indx-1] + prod\n",
"print(growing_sums.head())\n",
"print(growing_sums.tail())"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x7fc2f0f7f8d0>"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fc2f34e2940>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(time_current, growing_sums)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x7fc2f0e9b0b8>"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fc2f356f048>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(time_current, accel)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}