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Kentucky This file was generated on August 29, 2026 |
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Links and Resources¶
Where are the fracking locations in this state?¶
This is not an exhaustive set of wells in these counties; it is only those wells for which the operating company submits a chemical disclosure to FracFocus. In addition, this map omits disclosures for which location information is conflicting, such as the Latitude/Longitude values are outside of the reported county.
by county¶
by watershed¶
Applying simplification with tolerance: 500 meters
Number of disclosures per month¶
--------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In[10], line 15 11 gb3 = gb[gb.no_chem_recs].groupby('date').size() 12 # alldfv1 = master_df[~master_df.ingKeyPresent].groupby('DisclosureId',as_index=False)[['date','TotalBaseWaterVolume']].first() 13 # gbv1 = gb3.groupby('date').size() 14 allwk_sumv1 = gb3.resample("ME").sum() ---> 15 allwk_sumv1.plot(ax=ax,label='without chemical records'); 16 ax.legend(); 17 plt.tight_layout() 18 plt.savefig(os.path.join(hndl.browser_states_dir,state_file_handle,'number_disc_in_state.jpg')) File ~\anaconda3\envs\openClean\Lib\site-packages\pandas\plotting\_core.py:1185, in PlotAccessor.__call__(self, *args, **kwargs) 1182 label_name = label_kw or data.columns 1183 data.columns = label_name -> 1185 return plot_backend.plot(data, kind=kind, **kwargs) File ~\anaconda3\envs\openClean\Lib\site-packages\pandas\plotting\_matplotlib\__init__.py:71, in plot(data, kind, **kwargs) 69 kwargs["ax"] = getattr(ax, "left_ax", ax) 70 plot_obj = PLOT_CLASSES[kind](data, **kwargs) ---> 71 plot_obj.generate() 72 plt.draw_if_interactive() 73 return plot_obj.result File ~\anaconda3\envs\openClean\Lib\site-packages\pandas\plotting\_matplotlib\core.py:518, in MPLPlot.generate(self) 516 self._compute_plot_data() 517 fig = self.fig --> 518 self._make_plot(fig) 519 self._add_table() 520 self._make_legend() File ~\anaconda3\envs\openClean\Lib\site-packages\pandas\plotting\_matplotlib\core.py:1612, in LinePlot._make_plot(self, fig) 1608 if self._is_ts_plot(): 1609 # reset of xlim should be used for ts data 1610 # TODO: GH28021, should find a way to change view limit on xaxis 1611 lines = get_all_lines(ax) -> 1612 left, right = get_xlim(lines) 1613 ax.set_xlim(left, right) File ~\anaconda3\envs\openClean\Lib\site-packages\pandas\plotting\_matplotlib\tools.py:489, in get_xlim(lines) 487 for line in lines: 488 x = line.get_xdata(orig=False) --> 489 left = min(np.nanmin(x), left) 490 right = max(np.nanmax(x), right) 491 return left, right File ~\anaconda3\envs\openClean\Lib\site-packages\numpy\lib\_nanfunctions_impl.py:356, in nanmin(a, axis, out, keepdims, initial, where) 351 kwargs['where'] = where 353 if (type(a) is np.ndarray or type(a) is np.memmap) and a.dtype != np.object_: 354 # Fast, but not safe for subclasses of ndarray, or object arrays, 355 # which do not implement isnan (gh-9009), or fmin correctly (gh-8975) --> 356 res = np.fmin.reduce(a, axis=axis, out=out, **kwargs) 357 if np.isnan(res).any(): 358 warnings.warn("All-NaN slice encountered", RuntimeWarning, 359 stacklevel=2) ValueError: zero-size array to reduction operation fmin which has no identity
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Trade Secret designations¶
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Duplicate records¶
As of Aug. 2024, the disclosures of many operator companies had apparently unintentional duplicate records in them. Such duplicates can distort calculations of chemical quantity. In this section, we compare the current status of those records for this state with the baseline taken in Aug. 2024.