import plotly.express as px
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

Flight Data - Identifying the launch time

This is the 3rd notebook in the series. Earlier parts:

• ./010-video-export.html - for exporting still frames and timecodes for the videos
• ./020-video-analysis.html - for analyzing the video frames to match mission time with key events

baro = pd.read_csv('data/BarometerData-20250405-162645.csv')
baro = baro.iloc[11:]
baro = baro[baro['timestamp'] > 440000]
baro = baro.set_index('timestamp')
baro.head()

	time	pressure	altitude	average_altitude	temperature
timestamp
440033	16:20:54.830000	102139.593750	0.210183	0.046781	28.620001
440286	16:20:55.083000	102143.968750	-0.150846	0.055706	28.629999
440538	16:20:55.335000	102141.726562	0.034192	0.055847	28.650000
440792	16:20:55.589000	102138.843750	0.272032	0.047770	28.629999
441042	16:20:55.839000	102140.531250	0.132747	0.044345	28.639999

filtered_data = baro[(baro.index > 441500) & (baro.index < 443500)]['altitude']

fig = px.scatter(x=filtered_data.index, y=filtered_data.values, 
                 title="Rocket Altitude Measurements",
                 labels={"x": "Time (ms)", "y": "Altitude (m)"})

fig.update_traces(mode='lines+markers')
fig.update_xaxes(range=[441500, 443500])
fig.show()