dict_keys(['Fig1', 'Fig2', 'Fig3a_3b', 'Fig4', 'Fig5'])

<div>
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</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>countryname</th>
      <th>regionnum</th>
      <th>incomenum</th>
      <th>oilproducers</th>
      <th>av_perf0100_2021</th>
      <th>rank</th>
      <th>av_perf0100_2022</th>
      <th>CCE Performance</th>
      <th>Share of total</th>
      <th>Unnamed: 9</th>
      <th>...</th>
      <th>Unnamed: 16</th>
      <th>rank.3</th>
      <th>av_cceind20210100</th>
      <th>rank.4</th>
      <th>av_cceind20220100</th>
      <th>Unnamed: 21</th>
      <th>rank.5</th>
      <th>change in rank</th>
      <th>Unnamed: 24</th>
      <th>Unnamed: 25</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>Uganda 64.</td>
      <td>Sub-Saharan Africa</td>
      <td>Low Income</td>
      <td>0.0</td>
      <td>8.061891</td>
      <td>64.0</td>
      <td>8.097511</td>
      <td>4.048756</td>
      <td>0.260243</td>
      <td>-0.146257</td>
      <td>...</td>
      <td>0.146257</td>
      <td>59.0</td>
      <td>15.46242</td>
      <td>64.0</td>
      <td>15.55761</td>
      <td>15.557606</td>
      <td>65.0</td>
      <td>-1.0</td>
      <td>NaN</td>
      <td>NaN</td>
    </tr>
    <tr>
      <th>1</th>
      <td>Ethiopia 63.</td>
      <td>Sub-Saharan Africa</td>
      <td>Low Income</td>
      <td>0.0</td>
      <td>11.106590</td>
      <td>63.0</td>
      <td>11.108780</td>
      <td>5.55439</td>
      <td>0.321484</td>
      <td>-0.085016</td>
      <td>...</td>
      <td>0.085016</td>
      <td>57.0</td>
      <td>17.13467</td>
      <td>63.0</td>
      <td>17.27733</td>
      <td>17.277330</td>
      <td>64.0</td>
      <td>-1.0</td>
      <td>NaN</td>
      <td>NaN</td>
    </tr>
    <tr>
      <th>2</th>
      <td>Nigeria 62.</td>
      <td>Sub-Saharan Africa</td>
      <td>Middle Income</td>
      <td>1.0</td>
      <td>11.990210</td>
      <td>62.0</td>
      <td>11.361910</td>
      <td>5.680955</td>
      <td>0.296289</td>
      <td>-0.110211</td>
      <td>...</td>
      <td>0.110211</td>
      <td>55.0</td>
      <td>19.05157</td>
      <td>61.0</td>
      <td>19.17370</td>
      <td>19.173705</td>
      <td>63.0</td>
      <td>-2.0</td>
      <td>NaN</td>
      <td>NaN</td>
    </tr>
    <tr>
      <th>3</th>
      <td>Tanzania 61.</td>
      <td>Sub-Saharan Africa</td>
      <td>Low Income</td>
      <td>0.0</td>
      <td>14.799410</td>
      <td>61.0</td>
      <td>15.702160</td>
      <td>7.85108</td>
      <td>0.406883</td>
      <td>0.000383</td>
      <td>...</td>
      <td>-0.000384</td>
      <td>60.0</td>
      <td>18.51904</td>
      <td>62.0</td>
      <td>19.29565</td>
      <td>19.295645</td>
      <td>62.0</td>
      <td>0.0</td>
      <td>NaN</td>
      <td>NaN</td>
    </tr>
    <tr>
      <th>4</th>
      <td>Cameroon 60.</td>
      <td>Sub-Saharan Africa</td>
      <td>Middle Income</td>
      <td>0.0</td>
      <td>20.613290</td>
      <td>49.0</td>
      <td>22.859450</td>
      <td>11.429725</td>
      <td>0.522963</td>
      <td>0.116463</td>
      <td>...</td>
      <td>-0.116464</td>
      <td>64.0</td>
      <td>20.70525</td>
      <td>60.0</td>
      <td>21.85569</td>
      <td>21.855685</td>
      <td>61.0</td>
      <td>-1.0</td>
      <td>NaN</td>
      <td>NaN</td>
    </tr>
  </tbody>
</table>
<p>5 rows × 26 columns</p>
</div>

    countryname           regionnum      incomenum  oilproducers  \
0    Uganda 64.  Sub-Saharan Africa     Low Income           0.0   
1  Ethiopia 63.  Sub-Saharan Africa     Low Income           0.0   
2   Nigeria 62.  Sub-Saharan Africa  Middle Income           1.0   
3  Tanzania 61.  Sub-Saharan Africa     Low Income           0.0   
4  Cameroon 60.  Sub-Saharan Africa  Middle Income           0.0   

   av_perf0100_2021  rank  av_perf0100_2022 CCE Performance  Share of total  \
0          8.061891  64.0          8.097511        4.048756        0.260243   
1         11.106590  63.0         11.108780         5.55439        0.321484   
2         11.990210  62.0         11.361910        5.680955        0.296289   
3         14.799410  61.0         15.702160         7.85108        0.406883   
4         20.613290  49.0         22.859450       11.429725        0.522963   

   Unnamed: 9  ...  Unnamed: 16  rank.3  av_cceind20210100  rank.4  \
0   -0.146257  ...     0.146257    59.0           15.46242    64.0   
1   -0.085016  ...     0.085016    57.0           17.13467    63.0   
2   -0.110211  ...     0.110211    55.0           19.05157    61.0   
3    0.000383  ...    -0.000384    60.0           18.51904    62.0   
4    0.116463  ...    -0.116464    64.0           20.70525    60.0   

   av_cceind20220100  Unnamed: 21  rank.5  change in rank  Unnamed: 24  \
0           15.55761    15.557606    65.0            -1.0          NaN   
1           17.27733    17.277330    64.0            -1.0          NaN   
2           19.17370    19.173705    63.0            -2.0          NaN   
3           19.29565    19.295645    62.0             0.0          NaN   
4           21.85569    21.855685    61.0            -1.0          NaN   

   Unnamed: 25  
0          NaN  
1          NaN  
2          NaN  
3          NaN  
4          NaN  

[5 rows x 26 columns]

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        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>countryname</th>
      <th>CCE Performance</th>
      <th>CCE Enablers</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>Uganda 64.</td>
      <td>4.048756</td>
      <td>11.508850</td>
    </tr>
    <tr>
      <th>1</th>
      <td>Ethiopia 63.</td>
      <td>5.55439</td>
      <td>11.722940</td>
    </tr>
    <tr>
      <th>2</th>
      <td>Nigeria 62.</td>
      <td>5.680955</td>
      <td>13.492750</td>
    </tr>
    <tr>
      <th>3</th>
      <td>Tanzania 61.</td>
      <td>7.85108</td>
      <td>11.444565</td>
    </tr>
    <tr>
      <th>4</th>
      <td>Cameroon 60.</td>
      <td>11.429725</td>
      <td>10.425960</td>
    </tr>
  </tbody>
</table>
</div>

    countryname CCE Performance  CCE Enablers
0    Uganda 64.        4.048756     11.508850
1  Ethiopia 63.         5.55439     11.722940
2   Nigeria 62.        5.680955     13.492750
3  Tanzania 61.         7.85108     11.444565
4  Cameroon 60.       11.429725     10.425960

Vizly: AI-powered data analysis

Notebook

Make a horizontal stacked bar chart for each country in Fig1, with one section being the CCE Performance and the second being CCE Enablers