Datasets:
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Fix \"-\" in \"Collected_by\" Columns in full_master and Heliconius subsets\n",
"\n",
"See [discussion](https://huggingface.co/datasets/imageomics/Heliconius-Collection_Cambridge-Butterfly/discussions/7). I then tested each column that showed up as \"null\" in type on the dataset viewer (searching for df[col] == \"-\")."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# while main is commit 3264ec40dbc9db025e027ddb2abca0914cd6500f\n",
"df = pd.read_csv(\"https://huggingface.co/datasets/imageomics/Heliconius-Collection_Cambridge-Butterfly/resolve/main/img_master.csv\", low_memory= False)\n",
"df_heli = pd.read_csv(\"https://huggingface.co/datasets/imageomics/Heliconius-Collection_Cambridge-Butterfly/resolve/main/Heliconius_img_master.csv\", low_memory=False)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"column Collected_by has 62 instances of '-'\n"
]
}
],
"source": [
"for col in list(df.columns):\n",
" temp = df.loc[df[col] == \"-\"]\n",
" if temp.shape[0] > 0:\n",
" print(f\"column {col} has {temp.shape[0]} instances of '-'\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"column Collected_by has 62 instances of '-'\n"
]
}
],
"source": [
"for col in list(df_heli.columns):\n",
" temp = df_heli.loc[df_heli[col] == \"-\"]\n",
" if temp.shape[0] > 0:\n",
" print(f\"column {col} has {temp.shape[0]} instances of '-'\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Looks like we just need to fix the `Collected_by` column for both CSVs. We'll replace these with `null` so that it doesn't break the dataset viewer."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"df.loc[df[\"Collected_by\"] == \"-\", \"Collected_by\"] = np.nan\n",
"df_heli.loc[df_heli[\"Collected_by\"] == \"-\", \"Collected_by\"] = np.nan"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Now let's save the fix"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"df.to_csv(\"../img_master.csv\", index = False)\n",
"df_heli.to_csv(\"../Heliconius_img_master.csv\", index = False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "std",
"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": "3.11.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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