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# Created by https://www.toptal.com/developers/gitignore/api/macos,python
# Edit at https://www.toptal.com/developers/gitignore?templates=macos,python
### macOS ###
# General
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# Icon must end with two \r
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*.manifest
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*.mo
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*.log
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.scrapy
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# PyBuilder
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# intended to run in multiple environments; otherwise, check them in:
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#pdm.lock
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.pdm.toml
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celerybeat-schedule
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# SageMath parsed files
*.sage.py
# Environments
.env
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.spyderproject
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.mypy_cache/
.dmypy.json
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.pyre/
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.pytype/
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### Python Patch ###
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# End of https://www.toptal.com/developers/gitignore/api/macos,python

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# Setup
Install dependencies:
```bash
pip install -r requirements.txt
```
## Run
Open the notebook in Jupyter:
```bash
jupyter notebook
```

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Tc pH assay siderite.xlsx Normal file

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{
"cells": [
{
"cell_type": "markdown",
"id": "f5257869",
"metadata": {},
"source": [
"# Step 1 is to import Data. \n",
"Seems like it is possible to import ur Excel directly:"
]
},
{
"cell_type": "markdown",
"id": "003d5178",
"metadata": {},
"source": [
"## Here are the import. Not that important"
]
},
{
"cell_type": "code",
"execution_count": 47,
"id": "7594a3a3",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"from dataclasses import dataclass\n",
"from datetime import date, datetime"
]
},
{
"cell_type": "markdown",
"id": "c276e1f8",
"metadata": {},
"source": [
"## Here is the data"
]
},
{
"cell_type": "markdown",
"id": "6ee960c6",
"metadata": {},
"source": [
"### \"LSC raw data\" sheet has two tables"
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "87639af2-44c8-425f-bd0d-37348e1fbaa3",
"metadata": {},
"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>Position</th>\n",
" <th>Sample_ID</th>\n",
" <th>CPM</th>\n",
" <th>Efficiency</th>\n",
" <th>DPM im Vial</th>\n",
" <th>Bq im Vial</th>\n",
" <th>Error 2S%</th>\n",
" <th>Lumi %</th>\n",
" <th>TDCR</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>A01</td>\n",
" <td>blank</td>\n",
" <td>68.34</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>7.653</td>\n",
" <td>4.039</td>\n",
" <td>0.278</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>A02</td>\n",
" <td>Tc stock 10e-4M</td>\n",
" <td>65636.10</td>\n",
" <td>0.975</td>\n",
" <td>67331.40</td>\n",
" <td>1122.190</td>\n",
" <td>0.252</td>\n",
" <td>0.019</td>\n",
" <td>0.972</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>A03</td>\n",
" <td>Tc_sid_20min_4a</td>\n",
" <td>7069.88</td>\n",
" <td>0.975</td>\n",
" <td>7250.55</td>\n",
" <td>120.842</td>\n",
" <td>0.751</td>\n",
" <td>0.073</td>\n",
" <td>0.972</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>A04</td>\n",
" <td>Tc_sid_20min_5a</td>\n",
" <td>7887.32</td>\n",
" <td>0.977</td>\n",
" <td>8075.90</td>\n",
" <td>134.598</td>\n",
" <td>0.711</td>\n",
" <td>0.069</td>\n",
" <td>0.974</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>A05</td>\n",
" <td>Tc_sid_20min_6a</td>\n",
" <td>-17.61</td>\n",
" <td>0.802</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>8.882</td>\n",
" <td>6.663</td>\n",
" <td>0.757</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Position Sample_ID CPM Efficiency DPM im Vial Bq im Vial \\\n",
"0 A01 blank 68.34 NaN NaN NaN \n",
"1 A02 Tc stock 10e-4M 65636.10 0.975 67331.40 1122.190 \n",
"2 A03 Tc_sid_20min_4a 7069.88 0.975 7250.55 120.842 \n",
"3 A04 Tc_sid_20min_5a 7887.32 0.977 8075.90 134.598 \n",
"4 A05 Tc_sid_20min_6a -17.61 0.802 0.00 0.000 \n",
"\n",
" Error 2S% Lumi % TDCR \n",
"0 7.653 4.039 0.278 \n",
"1 0.252 0.019 0.972 \n",
"2 0.751 0.073 0.972 \n",
"3 0.711 0.069 0.974 \n",
"4 8.882 6.663 0.757 "
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"LSC_raw_data_part1 = pd.read_excel(\"Tc pH assay siderite.xlsx\", sheet_name=\"LSC raw data\", nrows=14)\n",
"LSC_raw_data_part1.head()"
]
},
{
"cell_type": "markdown",
"id": "09585c9a",
"metadata": {},
"source": [
"The second table starts at 18th row, so I had to skip some rows and also the column A for table 2 is empty, so I did the `usecols` range"
]
},
{
"cell_type": "code",
"execution_count": 43,
"id": "ba4cf093",
"metadata": {},
"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>Unnamed: 1</th>\n",
" <th>Unnamed: 2</th>\n",
" <th>Unnamed: 3</th>\n",
" <th>Unnamed: 4</th>\n",
" <th>Unnamed: 5</th>\n",
" <th>Unnamed: 6</th>\n",
" <th>Unnamed: 7</th>\n",
" <th>Unnamed: 8</th>\n",
" <th>Unnamed: 9</th>\n",
" <th>Unnamed: 10</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Sample_ID</td>\n",
" <td>CPM</td>\n",
" <td>Efficiency</td>\n",
" <td>DPM im Vial</td>\n",
" <td>LSC, mL</td>\n",
" <td>Tc aliquot, mL</td>\n",
" <td>Vial, Bq/ml</td>\n",
" <td>Sample, Bq/ml</td>\n",
" <td>Sample [99Tc], mM</td>\n",
" <td>Sample [99Tc], mM</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Tc stock 10e-4M</td>\n",
" <td>65636.1</td>\n",
" <td>0.975</td>\n",
" <td>67331.4</td>\n",
" <td>5</td>\n",
" <td>0.2</td>\n",
" <td>215.805769</td>\n",
" <td>5610.95</td>\n",
" <td>0.089547</td>\n",
" <td>0.00009</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Unnamed: 1 Unnamed: 2 Unnamed: 3 Unnamed: 4 Unnamed: 5 \\\n",
"0 Sample_ID CPM Efficiency DPM im Vial LSC, mL \n",
"1 Tc stock 10e-4M 65636.1 0.975 67331.4 5 \n",
"\n",
" Unnamed: 6 Unnamed: 7 Unnamed: 8 Unnamed: 9 \\\n",
"0 Tc aliquot, mL Vial, Bq/ml Sample, Bq/ml Sample [99Tc], mM \n",
"1 0.2 215.805769 5610.95 0.089547 \n",
"\n",
" Unnamed: 10 \n",
"0 Sample [99Tc], mM \n",
"1 0.00009 "
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"LSC_raw_data_part2 = pd.read_excel(\"Tc pH assay siderite.xlsx\", sheet_name=\"LSC raw data\",skiprows=16, usecols=\"B:K\")\n",
"LSC_raw_data_part2.head()"
]
},
{
"cell_type": "markdown",
"id": "9f781886",
"metadata": {},
"source": [
"### LSC data"
]
},
{
"cell_type": "code",
"execution_count": 49,
"id": "0849ddc0",
"metadata": {},
"outputs": [],
"source": [
"@dataclass\n",
"class LSC_data:\n",
" description: str\n",
" measured_date: date\n",
" data_blank: pd.DataFrame = None\n",
" data_stock: pd.DataFrame = None\n",
" data_20min: pd.DataFrame = None"
]
},
{
"cell_type": "code",
"execution_count": 50,
"id": "28c3d5a6",
"metadata": {},
"outputs": [],
"source": [
"LSC_data_TC_11_03_26 = LSC_data(\n",
" description=\"1E-5 M Tc with 1.3 g/L of siderite, after 30 min\",\n",
" measured_date=datetime.strptime(\"11.03.2026\", \"%d.%m.%Y\").date(),\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "d6ee04cb",
"metadata": {},
"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>Positions</th>\n",
" <th>Sample ID</th>\n",
" <th>cpm</th>\n",
" <th>LSC, mL</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>A01</td>\n",
" <td>blank</td>\n",
" <td>68.34</td>\n",
" <td>5</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Positions Sample ID cpm LSC, mL\n",
"0 A01 blank 68.34 5"
]
},
"execution_count": 51,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"LSC_data_TC_11_03_26.data_blank = pd.read_excel(\"Tc pH assay siderite.xlsx\", sheet_name=\"LSC data\",nrows=1, skiprows=4, usecols=\"A:C, F\")\n",
"LSC_data_TC_11_03_26.data_blank"
]
},
{
"cell_type": "code",
"execution_count": 67,
"id": "64965457",
"metadata": {},
"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>Positions</th>\n",
" <th>Sample ID</th>\n",
" <th>cpm</th>\n",
" <th>Efficiency</th>\n",
" <th>DPM in vial</th>\n",
" <th>LSC, mL</th>\n",
" <th>Tc aliquot, mL</th>\n",
" <th>Vial, Bq/ml</th>\n",
" <th>Sample, Bq/ml</th>\n",
" <th>Sample [99Tc], M</th>\n",
" <th>LSC waste, Bq/mL</th>\n",
" <th>Bq, solid waste</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>A02</td>\n",
" <td>Tc stock 10e-4M</td>\n",
" <td>65636.1</td>\n",
" <td>0.975</td>\n",
" <td>67331.4</td>\n",
" <td>5</td>\n",
" <td>0.2</td>\n",
" <td>215.805769</td>\n",
" <td>5610.95</td>\n",
" <td>0.00009</td>\n",
" <td>215.805769</td>\n",
" <td>28054.75</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Positions Sample ID cpm Efficiency DPM in vial LSC, mL \\\n",
"0 A02 Tc stock 10e-4M 65636.1 0.975 67331.4 5 \n",
"\n",
" Tc aliquot, mL Vial, Bq/ml Sample, Bq/ml Sample [99Tc], M \\\n",
"0 0.2 215.805769 5610.95 0.00009 \n",
"\n",
" LSC waste, Bq/mL Bq, solid waste \n",
"0 215.805769 28054.75 "
]
},
"execution_count": 67,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"LSC_data_TC_11_03_26.data_stock = pd.read_excel(\"Tc pH assay siderite.xlsx\", sheet_name=\"LSC data\", skiprows=[0,1,2,3,5], nrows=1)\n",
"LSC_data_TC_11_03_26.data_stock"
]
},
{
"cell_type": "code",
"execution_count": 71,
"id": "6a867236",
"metadata": {},
"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>Positions</th>\n",
" <th>Sample ID</th>\n",
" <th>cpm</th>\n",
" <th>Efficiency</th>\n",
" <th>DPM in vial</th>\n",
" <th>LSC, mL</th>\n",
" <th>Tc aliquot, mL</th>\n",
" <th>Vial, Bq/ml</th>\n",
" <th>Sample, Bq/ml</th>\n",
" <th>Sample [99Tc], M</th>\n",
" <th>LSC waste, Bq/mL</th>\n",
" <th>Bq, solid waste</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>A03</td>\n",
" <td>Tc_sid_20min_4a</td>\n",
" <td>7069.88</td>\n",
" <td>0.975</td>\n",
" <td>7250.550</td>\n",
" <td>5</td>\n",
" <td>0.2</td>\n",
" <td>23.238942</td>\n",
" <td>604.212500</td>\n",
" <td>9.642853e-06</td>\n",
" <td>23.238942</td>\n",
" <td>-215.587500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>A04</td>\n",
" <td>Tc_sid_20min_5a</td>\n",
" <td>7887.32</td>\n",
" <td>0.977</td>\n",
" <td>8075.900</td>\n",
" <td>5</td>\n",
" <td>0.2</td>\n",
" <td>25.884295</td>\n",
" <td>672.991667</td>\n",
" <td>1.074053e-05</td>\n",
" <td>25.884295</td>\n",
" <td>-559.483333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>A05</td>\n",
" <td>Tc_sid_20min_6a</td>\n",
" <td>-17.61</td>\n",
" <td>0.802</td>\n",
" <td>0.000</td>\n",
" <td>5</td>\n",
" <td>0.2</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000</td>\n",
" <td>2805.475000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>A06</td>\n",
" <td>Tc_sid_20min_6b</td>\n",
" <td>1760.91</td>\n",
" <td>0.970</td>\n",
" <td>1814.950</td>\n",
" <td>5</td>\n",
" <td>0.2</td>\n",
" <td>5.817147</td>\n",
" <td>151.245833</td>\n",
" <td>2.413789e-06</td>\n",
" <td>5.817147</td>\n",
" <td>2049.245833</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>B01</td>\n",
" <td>Tc_sid_20min_8a</td>\n",
" <td>93.14</td>\n",
" <td>0.886</td>\n",
" <td>105.150</td>\n",
" <td>5</td>\n",
" <td>0.2</td>\n",
" <td>0.337019</td>\n",
" <td>8.762500</td>\n",
" <td>1.398440e-07</td>\n",
" <td>0.337019</td>\n",
" <td>2761.662500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>B02</td>\n",
" <td>Tc_sid_20min_8b</td>\n",
" <td>425.42</td>\n",
" <td>0.900</td>\n",
" <td>472.848</td>\n",
" <td>5</td>\n",
" <td>0.2</td>\n",
" <td>1.515538</td>\n",
" <td>39.404000</td>\n",
" <td>6.288632e-07</td>\n",
" <td>1.515538</td>\n",
" <td>2608.455000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>B03</td>\n",
" <td>Tc_sid_20min_10a</td>\n",
" <td>64.61</td>\n",
" <td>0.918</td>\n",
" <td>70.412</td>\n",
" <td>5</td>\n",
" <td>0.2</td>\n",
" <td>0.225679</td>\n",
" <td>5.867667</td>\n",
" <td>9.364429e-08</td>\n",
" <td>0.225679</td>\n",
" <td>2776.136667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>B04</td>\n",
" <td>Tc_sid_20min_10b</td>\n",
" <td>-38.33</td>\n",
" <td>0.791</td>\n",
" <td>0.000</td>\n",
" <td>5</td>\n",
" <td>0.2</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000</td>\n",
" <td>2805.475000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>B05</td>\n",
" <td>Tc_sid_20min_12a</td>\n",
" <td>205.38</td>\n",
" <td>0.930</td>\n",
" <td>220.944</td>\n",
" <td>5</td>\n",
" <td>0.2</td>\n",
" <td>0.708154</td>\n",
" <td>18.412000</td>\n",
" <td>2.938440e-07</td>\n",
" <td>0.708154</td>\n",
" <td>2713.415000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>B06</td>\n",
" <td>Tc_sid_20min_12b</td>\n",
" <td>-30.53</td>\n",
" <td>0.782</td>\n",
" <td>0.000</td>\n",
" <td>5</td>\n",
" <td>0.2</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000</td>\n",
" <td>2805.475000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Positions Sample ID cpm Efficiency DPM in vial LSC, mL \\\n",
"0 A03 Tc_sid_20min_4a 7069.88 0.975 7250.550 5 \n",
"1 A04 Tc_sid_20min_5a 7887.32 0.977 8075.900 5 \n",
"2 A05 Tc_sid_20min_6a -17.61 0.802 0.000 5 \n",
"3 A06 Tc_sid_20min_6b 1760.91 0.970 1814.950 5 \n",
"4 B01 Tc_sid_20min_8a 93.14 0.886 105.150 5 \n",
"5 B02 Tc_sid_20min_8b 425.42 0.900 472.848 5 \n",
"6 B03 Tc_sid_20min_10a 64.61 0.918 70.412 5 \n",
"7 B04 Tc_sid_20min_10b -38.33 0.791 0.000 5 \n",
"8 B05 Tc_sid_20min_12a 205.38 0.930 220.944 5 \n",
"9 B06 Tc_sid_20min_12b -30.53 0.782 0.000 5 \n",
"\n",
" Tc aliquot, mL Vial, Bq/ml Sample, Bq/ml Sample [99Tc], M \\\n",
"0 0.2 23.238942 604.212500 9.642853e-06 \n",
"1 0.2 25.884295 672.991667 1.074053e-05 \n",
"2 0.2 0.000000 0.000000 0.000000e+00 \n",
"3 0.2 5.817147 151.245833 2.413789e-06 \n",
"4 0.2 0.337019 8.762500 1.398440e-07 \n",
"5 0.2 1.515538 39.404000 6.288632e-07 \n",
"6 0.2 0.225679 5.867667 9.364429e-08 \n",
"7 0.2 0.000000 0.000000 0.000000e+00 \n",
"8 0.2 0.708154 18.412000 2.938440e-07 \n",
"9 0.2 0.000000 0.000000 0.000000e+00 \n",
"\n",
" LSC waste, Bq/mL Bq, solid waste \n",
"0 23.238942 -215.587500 \n",
"1 25.884295 -559.483333 \n",
"2 0.000000 2805.475000 \n",
"3 5.817147 2049.245833 \n",
"4 0.337019 2761.662500 \n",
"5 1.515538 2608.455000 \n",
"6 0.225679 2776.136667 \n",
"7 0.000000 2805.475000 \n",
"8 0.708154 2713.415000 \n",
"9 0.000000 2805.475000 "
]
},
"execution_count": 71,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"LSC_data_TC_11_03_26.data_20min = pd.read_excel(\"Tc pH assay siderite.xlsx\", sheet_name=\"LSC data\",skiprows=[0,1,2,3,5,6], nrows=10)\n",
"LSC_data_TC_11_03_26.data_20min"
]
},
{
"cell_type": "code",
"execution_count": 73,
"id": "ca670fd3",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"LSC waste, Bq/mL 57.726776\n",
"Bq, solid waste 20550.269167\n",
"dtype: float64"
]
},
"execution_count": 73,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"LSC_data_TC_11_03_26.data_20min[[\"LSC waste, Bq/mL\", \"Bq, solid waste\"]].sum()\n"
]
},
{
"cell_type": "markdown",
"id": "d01c706b",
"metadata": {},
"source": [
"# Step 2: Do data anal"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0bb6ad81",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "d658c450",
"metadata": {},
"source": [
"# Step 3: Plot the data"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "venv",
"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": "3.14.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

2
requirements.txt Normal file
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@@ -0,0 +1,2 @@
pandas
openpyxl