code/rr_notebooks/epa_pm_data.ipynb

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    "Code from Helen to download and filter pm2.5 data"
   ]
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   "source": [
    "### Filtering this EPA-sourced kaggle data down to the metrics we care about\n",
    "Download original [here](https://www.kaggle.com/epa/hazardous-air-pollutants?select=epa_hap_daily_summary.csv)  \n",
    "No other cleaning performed yet - this is just so you can download and see what I'm seeing."
   ]
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   "cell_type": "code",
   "execution_count": 61,
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   "source": [
    "data = pd.read_csv('../scratch_data/epa_hap_daily_summary.csv')"
   ]
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   "execution_count": 62,
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   "source": [
    "# drop States outside of focus area\n",
    "keep_states = ['California', 'Washington', 'Oregon', 'Arizona', 'Nevada', 'Idaho', 'Utah']\n",
    "data = data.loc[new_kaggle['state_name'].isin(keep_states)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop pollutants outside of focus area\n",
    "data = data.loc[new_kaggle['parameter_name'].str.contains('2.5')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
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   "source": [
    "# specify date range\n",
    "data = data.loc[new_kaggle['date_local']>='2010-01-01']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # update with your filepath, label very descriptively\n",
    "# data.to_csv('../scratch_data/pm2.5_epa_2010_2017.csv', index=False)"
   ]
  }
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