california-one-pager.ipynb

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  {
   "cell_type": "code",
   "execution_count": 22,
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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import microdf as mdf\n",
    "import plotly.express as px\n",
    "import ubicenter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "p = pd.read_csv(\"data/original/spm_2010_2020/cps.csv.gz\")\n",
    "p.columns = p.columns.str.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "p[\"poor\"] = p.spmtotres < p.spmthresh\n",
    "p[\"child\"] = p.age < 18\n",
    "p[\"child_poor\"] = np.where(p.child, p.poor, np.nan)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
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   "source": [
    "CA = 6\n",
    "DC = 11\n",
    "# Children, exclude DC.\n",
    "state_year = mdf.weighted_mean(p[(p.age < 18) & (p.statefip != DC)], \"poor\", \"asecwt\", groupby=[\"year\", \"statefip\"]).reset_index().rename(columns={0: \"child_pov\"})\n",
    "year = mdf.weighted_mean(p[(p.age < 18)], \"poor\", \"asecwt\", groupby=[\"year\"]).reset_index().rename(columns={0: \"child_pov\"})"
   ]
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   "source": [
    "state_year.statefip.nunique()"
   ]
  },
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   "execution_count": 20,
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       "     year  statefip  child_pov\n",
       "533  2020        27   0.042098\n",
       "522  2020        16   0.053517\n",
       "539  2020        33   0.060370\n",
       "529  2020        23   0.066637\n",
       "554  2020        49   0.066776\n",
       "535  2020        29   0.070572\n",
       "547  2020        41   0.071768\n",
       "544  2020        38   0.073916\n",
       "557  2020        53   0.074165\n",
       "536  2020        30   0.074190\n",
       "526  2020        20   0.078439\n",
       "531  2020        25   0.078849\n",
       "559  2020        55   0.079337\n",
       "560  2020        56   0.085281\n",
       "549  2020        44   0.088797\n",
       "546  2020        40   0.090892\n",
       "548  2020        42   0.091364\n",
       "537  2020        31   0.094087\n",
       "558  2020        54   0.094503\n",
       "538  2020        32   0.097351\n",
       "523  2020        17   0.098176\n",
       "516  2020         9   0.098936\n",
       "527  2020        21   0.099768\n",
       "530  2020        24   0.100420\n",
       "525  2020        19   0.101841\n",
       "532  2020        26   0.107279\n",
       "524  2020        18   0.108443\n",
       "540  2020        34   0.110433\n",
       "556  2020        51   0.111444\n",
       "552  2020        47   0.111791\n",
       "517  2020        10   0.111865\n",
       "513  2020         5   0.113091\n",
       "545  2020        39   0.114909\n",
       "515  2020         8   0.116521\n",
       "551  2020        46   0.117038\n",
       "511  2020         2   0.119014\n",
       "510  2020         1   0.123166\n",
       "553  2020        48   0.124921\n",
       "521  2020        15   0.131116\n",
       "541  2020        35   0.133241\n",
       "512  2020         4   0.138461\n",
       "520  2020        13   0.138556\n",
       "555  2020        50   0.138618\n",
       "518  2020        11   0.139931\n",
       "550  2020        45   0.142575\n",
       "543  2020        37   0.146386\n",
       "519  2020        12   0.149512\n",
       "542  2020        36   0.174704\n",
       "534  2020        28   0.178377\n",
       "528  2020        22   0.185576\n",
       "514  2020         6   0.187214"
      ],
      "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>year</th>\n      <th>statefip</th>\n      <th>child_pov</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>533</th>\n      <td>2020</td>\n      <td>27</td>\n      <td>0.042098</td>\n    </tr>\n    <tr>\n      <th>522</th>\n      <td>2020</td>\n      <td>16</td>\n      <td>0.053517</td>\n    </tr>\n    <tr>\n      <th>539</th>\n      <td>2020</td>\n      <td>33</td>\n      <td>0.060370</td>\n    </tr>\n    <tr>\n      <th>529</th>\n      <td>2020</td>\n      <td>23</td>\n      <td>0.066637</td>\n    </tr>\n    <tr>\n      <th>554</th>\n      <td>2020</td>\n      <td>49</td>\n      <td>0.066776</td>\n    </tr>\n    <tr>\n      <th>535</th>\n      <td>2020</td>\n      <td>29</td>\n      <td>0.070572</td>\n    </tr>\n    <tr>\n      <th>547</th>\n      <td>2020</td>\n      <td>41</td>\n      <td>0.071768</td>\n    </tr>\n    <tr>\n      <th>544</th>\n      <td>2020</td>\n      <td>38</td>\n      <td>0.073916</td>\n    </tr>\n    <tr>\n      <th>557</th>\n      <td>2020</td>\n      <td>53</td>\n      <td>0.074165</td>\n    </tr>\n    <tr>\n      <th>536</th>\n      <td>2020</td>\n      <td>30</td>\n      <td>0.074190</td>\n    </tr>\n    <tr>\n      <th>526</th>\n      <td>2020</td>\n      <td>20</td>\n      <td>0.078439</td>\n    </tr>\n    <tr>\n      <th>531</th>\n      <td>2020</td>\n      <td>25</td>\n      <td>0.078849</td>\n    </tr>\n    <tr>\n      <th>559</th>\n      <td>2020</td>\n      <td>55</td>\n      <td>0.079337</td>\n    </tr>\n    <tr>\n      <th>560</th>\n      <td>2020</td>\n      <td>56</td>\n      <td>0.085281</td>\n    </tr>\n    <tr>\n      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<td>24</td>\n      <td>0.100420</td>\n    </tr>\n    <tr>\n      <th>525</th>\n      <td>2020</td>\n      <td>19</td>\n      <td>0.101841</td>\n    </tr>\n    <tr>\n      <th>532</th>\n      <td>2020</td>\n      <td>26</td>\n      <td>0.107279</td>\n    </tr>\n    <tr>\n      <th>524</th>\n      <td>2020</td>\n      <td>18</td>\n      <td>0.108443</td>\n    </tr>\n    <tr>\n      <th>540</th>\n      <td>2020</td>\n      <td>34</td>\n      <td>0.110433</td>\n    </tr>\n    <tr>\n      <th>556</th>\n      <td>2020</td>\n      <td>51</td>\n      <td>0.111444</td>\n    </tr>\n    <tr>\n      <th>552</th>\n      <td>2020</td>\n      <td>47</td>\n      <td>0.111791</td>\n    </tr>\n    <tr>\n      <th>517</th>\n      <td>2020</td>\n      <td>10</td>\n      <td>0.111865</td>\n    </tr>\n    <tr>\n      <th>513</th>\n      <td>2020</td>\n      <td>5</td>\n      <td>0.113091</td>\n    </tr>\n    <tr>\n      <th>545</th>\n      <td>2020</td>\n      <td>39</td>\n      <td>0.114909</td>\n    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     },
     "metadata": {},
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   "source": [
    "state_year[state_year.year == 2020].sort_values(\"child_pov\")"
   ]
  },
  {
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           "bgcolor": "#E5ECF6",
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   ],
   "source": [
    "fig = px.line(year, \"year\", \"child_pov\", title=\"US child poverty rate\")\n",
    "fig.update_layout(yaxis_tickformat=\"%\", xaxis_title=\"\", yaxis_title=\"\")\n",
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            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "font": {
          "size": 20
         },
         "text": "California's child poverty rate ranking"
        },
        "width": 800,
        "xaxis": {
         "anchor": "y",
         "domain": [
          0,
          1
         ],
         "tickfont": {
          "size": 14
         },
         "title": {
          "font": {
           "color": "black",
           "size": 16
          },
          "text": ""
         }
        },
        "yaxis": {
         "anchor": "x",
         "domain": [
          0,
          1
         ],
         "tickfont": {
          "size": 14
         },
         "title": {
          "font": {
           "color": "black",
           "size": 16
          },
          "text": ""
         }
        }
       }
      }
     },
     "metadata": {}
    }
   ],
   "source": [
    "fig = px.bar(state_year[state_year.statefip == CA], \"year\", \"child_pov_rank\", title=\"California's child poverty rate ranking\")\n",
    "fig.update_layout(xaxis_title=\"\", yaxis_title=\"\")\n",
    "ubicenter.format_fig(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ]
}