├── README.md
├── competitions
└── Home-Credit-Default-Risk
│ └── README.md
├── datasets-notebooks
├── robocall-complaints
│ ├── README.md
│ └── profilereport.html
└── world-foodfeed-production
│ └── README.md
├── LICENSE
├── .gitignore
└── environment.yml
/README.md:
--------------------------------------------------------------------------------
1 | # Kaggle Notebooks
2 |
3 | [](https://mybinder.org/v2/gh/andersy005/kaggle-notebooks/master)
4 |
--------------------------------------------------------------------------------
/competitions/Home-Credit-Default-Risk/README.md:
--------------------------------------------------------------------------------
1 | # Home Credit Default Risk
2 |
3 | Can you predict how capable each applicant is of repaying a loan?
4 |
5 |
6 | ## Data
7 |
8 | 
--------------------------------------------------------------------------------
/datasets-notebooks/robocall-complaints/README.md:
--------------------------------------------------------------------------------
1 | # [Robocall Complaints](https://www.kaggle.com/fcc/robocall-complaints)
2 |
3 | **Consumer complaints filed with the FCC**
4 |
5 | Individual informal consumer complaint data detailing complaints filed with the Consumer Help Center beginning October 31, 2014. This data represents information selected by the consumer. The FCC does not verify the facts alleged in these complaints.
6 |
7 | This dataset contains everything you need to analyze the jerk companies who call during dinner: time, mode of communication, logged phone number (of the hassler), and what they were trying to do.
8 |
9 | ### Acknowledgements
10 |
11 | This dataset was kindly made available by the FCC. You can find [the original dataset here][1].
12 |
13 |
14 | [1]: https://opendata.fcc.gov/Consumer/CGB-Consumer-Complaints-Data/3xyp-aqkj
--------------------------------------------------------------------------------
/LICENSE:
--------------------------------------------------------------------------------
1 | MIT License
2 |
3 | Copyright (c) 2018 Anderson Banihirwe
4 |
5 | Permission is hereby granted, free of charge, to any person obtaining a copy
6 | of this software and associated documentation files (the "Software"), to deal
7 | in the Software without restriction, including without limitation the rights
8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 |
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 |
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 |
--------------------------------------------------------------------------------
/.gitignore:
--------------------------------------------------------------------------------
1 | # Byte-compiled / optimized / DLL files
2 | __pycache__/
3 | *.py[cod]
4 | *$py.class
5 |
6 | # C extensions
7 | *.so
8 |
9 | # Distribution / packaging
10 | .Python
11 | env/
12 | build/
13 | develop-eggs/
14 | dist/
15 | downloads/
16 | eggs/
17 | .eggs/
18 | lib/
19 | lib64/
20 | parts/
21 | sdist/
22 | var/
23 | wheels/
24 | *.egg-info/
25 | .installed.cfg
26 | *.egg
27 |
28 | # PyInstaller
29 | # Usually these files are written by a python script from a template
30 | # before PyInstaller builds the exe, so as to inject date/other infos into it.
31 | *.manifest
32 | *.spec
33 |
34 | # Installer logs
35 | pip-log.txt
36 | pip-delete-this-directory.txt
37 |
38 | # Unit test / coverage reports
39 | htmlcov/
40 | .tox/
41 | .coverage
42 | .coverage.*
43 | .cache
44 | nosetests.xml
45 | coverage.xml
46 | *.cover
47 | .hypothesis/
48 |
49 | # Translations
50 | *.mo
51 | *.pot
52 |
53 | # Django stuff:
54 | *.log
55 | local_settings.py
56 |
57 | # Flask stuff:
58 | instance/
59 | .webassets-cache
60 |
61 | # Scrapy stuff:
62 | .scrapy
63 |
64 | # Sphinx documentation
65 | docs/_build/
66 |
67 | # PyBuilder
68 | target/
69 |
70 | # Jupyter Notebook
71 | .ipynb_checkpoints
72 |
73 | # pyenv
74 | .python-version
75 |
76 | # celery beat schedule file
77 | celerybeat-schedule
78 |
79 | # SageMath parsed files
80 | *.sage.py
81 |
82 | # dotenv
83 | .env
84 |
85 | # virtualenv
86 | .venv
87 | venv/
88 | ENV/
89 |
90 | # Spyder project settings
91 | .spyderproject
92 | .spyproject
93 |
94 | # Rope project settings
95 | .ropeproject
96 |
97 | # mkdocs documentation
98 | /site
99 |
100 | # mypy
101 | .mypy_cache/
102 |
--------------------------------------------------------------------------------
/datasets-notebooks/world-foodfeed-production/README.md:
--------------------------------------------------------------------------------
1 |
2 |
3 | [Who eats the food we grow?
4 | Worldwide food\feed production and distribution, 1961-2013 ](https://www.kaggle.com/dorbicycle/world-foodfeed-production)
5 |
6 | ### Context
7 |
8 | Our world population is expected to grow from [7.3 billion today to 9.7 billion in the year 2050][1]. Finding solutions for feeding the growing world population has become a hot topic for [food and agriculture organizations][2], [entrepreneurs][3] and [philanthropists][4]. These solutions range from changing the way we [grow our food][5] to changing the [way we eat][6]. To make things harder, the world's climate is changing and it is both affecting and affected by the way we grow our food – agriculture.
9 | **This dataset provides an insight on our worldwide food production** - focusing on a comparison between food produced for human consumption and feed produced for animals.
10 |
11 |
12 |
13 | ### Content
14 |
15 | The Food and Agriculture Organization of the United Nations provides [free access to food and agriculture data][7] for over 245 countries and territories, from the year 1961 to the most recent update (depends on the dataset). One dataset from the FAO's database is the Food Balance Sheets. It presents a comprehensive picture of the pattern of a country's food supply during a specified reference period, the last time an update was loaded to the FAO database was in 2013. The food balance sheet shows for each food item the sources of supply and its utilization. This chunk of the dataset is focused on two utilizations of each food item available:
16 |
17 | - **Food** - refers to the total amount of the food item available as human food during the reference period.
18 | - **Feed** - refers to the quantity of the food item available for feeding to the livestock and poultry during the reference period.
19 |
20 | ### Acknowledgements
21 |
22 | This dataset was meticulously gathered, organized and published by the Food and Agriculture Organization of the United Nations.
23 |
24 | ### Inspiration
25 |
26 | Animal agriculture and factory farming is a a growing interest of the public and of world leaders.
27 |
28 | - Can you find interesting outliers in the data?
29 | - What are the fastest growing countries in terms of food production\consumption?
30 | - Compare between food and feed consumption.
31 |
32 | [1]: http://www.un.org/en/development/desa/news/population/2015-report.html
33 | [2]: http://www.fao.org/fileadmin/templates/wsfs/docs/expert_paper/How_to_Feed_the_World_in_2050.pdf
34 | [3]: https://www.entrepreneur.com/article/251515
35 | [4]: https://canwefeedtheworld.wordpress.com/tag/bill-gates/
36 | [5]: https://www.forbes.com/sites/christinatroitino/2017/08/24/memphis-meats-lab-grown-meat-raises-17m-with-help-from-bill-gates-and-richard-branson/#2f8186d43fd0
37 | [6]: https://www.peta.org/issues/animals-used-for-food/global-warming/
38 | [7]: http://www.fao.org/faostat/en/#home
39 |
--------------------------------------------------------------------------------
/environment.yml:
--------------------------------------------------------------------------------
1 | name: dl
2 | channels:
3 | - ioam
4 | - pytorch
5 | - anaconda
6 | - conda-forge
7 | - defaults
8 | dependencies:
9 | - cudatoolkit=9.0=h13b8566_0
10 | - attrs=17.4.0=py_0
11 | - backcall=0.1.0=py_0
12 | - blas=1.1=openblas
13 | - bleach=2.1.3=py_0
14 | - bokeh=0.12.15=py36_0
15 | - boost=1.66.0=py36_1
16 | - boost-cpp=1.66.0=1
17 | - bottleneck=1.2.1=py36_1
18 | - bzip2=1.0.6=1
19 | - cairo=1.14.10=0
20 | - click=6.7=py_1
21 | - click-plugins=1.0.3=py36_0
22 | - cligj=0.4.0=py36_0
23 | - cloudpickle=0.5.2=py_0
24 | - cryptography=2.2.1=py36_0
25 | - curl=7.59.0=1
26 | - cycler=0.10.0=py36_0
27 | - cytoolz=0.9.0.1=py36_0
28 | - dask=0.17.2=py_0
29 | - dask-core=0.17.2=py_0
30 | - dask-glm=0.1.0=0
31 | - dask-ml=0.4.1=py36_0
32 | - dask-searchcv=0.2.0=py_0
33 | - dbus=1.10.22=0
34 | - decorator=4.2.1=py36_0
35 | - descartes=1.1.0=py_1
36 | - distributed=1.21.6=py36_0
37 | - entrypoints=0.2.3=py36_1
38 | - expat=2.2.5=0
39 | - fastparquet=0.1.5=py36_0
40 | - fiona=1.7.11=py36_3
41 | - fontconfig=2.12.6=0
42 | - freetype=2.8.1=0
43 | - freexl=1.0.5=0
44 | - gdal=2.2.4=py36_0
45 | - geopandas=0.3.0=py36_0
46 | - geotiff=1.4.2=1
47 | - gettext=0.19.8.1=0
48 | - giflib=5.1.4=0
49 | - glib=2.55.0=0
50 | - gmp=6.1.2=0
51 | - gst-plugins-base=1.8.0=0
52 | - gstreamer=1.8.0=1
53 | - h5netcdf=0.5.1=py_0
54 | - h5py=2.7.1=py36_2
55 | - hdf4=4.2.13=0
56 | - hdf5=1.10.1=2
57 | - heapdict=1.0.0=py36_0
58 | - html5lib=1.0.1=py_0
59 | - icu=58.2=0
60 | - imageio=2.3.0=py36_0
61 | - ipykernel=4.8.2=py36_0
62 | - ipython=6.3.1=py36_0
63 | - ipython_genutils=0.2.0=py36_0
64 | - jedi=0.11.1=py36_0
65 | - jinja2=2.10=py36_0
66 | - joblib=0.11=py36_0
67 | - jpeg=9b=2
68 | - json-c=0.12.1=0
69 | - jsonschema=2.6.0=py36_1
70 | - jupyter_client=5.2.3=py36_0
71 | - jupyter_contrib_core=0.3.3=py36_1
72 | - jupyter_contrib_nbextensions=0.5.0=py36_0
73 | - jupyter_core=4.4.0=py_0
74 | - jupyter_highlight_selected_word=0.2.0=py36_0
75 | - jupyter_latex_envs=1.4.4=py36_0
76 | - jupyter_nbextensions_configurator=0.4.0=py36_0
77 | - jupyterlab=0.31.12=py36_1
78 | - jupyterlab_launcher=0.10.5=py36_0
79 | - kealib=1.4.7=4
80 | - kiwisolver=1.0.1=py36_1
81 | - krb5=1.14.6=0
82 | - libdap4=3.18.3=2
83 | - libffi=3.2.1=3
84 | - libgdal=2.2.4=1
85 | - libgpuarray=0.7.5=0
86 | - libiconv=1.15=0
87 | - libkml=1.3.0=6
88 | - libnetcdf=4.5.0=3
89 | - libpng=1.6.34=0
90 | - libpq=9.6.3=0
91 | - libsodium=1.0.16=0
92 | - libspatialindex=1.8.5=1
93 | - libspatialite=4.3.0a=19
94 | - libssh2=1.8.0=2
95 | - libtiff=4.0.9=0
96 | - libxcb=1.13=0
97 | - libxml2=2.9.8=0
98 | - llvmlite=0.21.0=py36_0
99 | - locket=0.2.0=py36_1
100 | - mako=1.0.7=py36_0
101 | - markupsafe=1.0=py36_0
102 | - matplotlib=2.2.2=py36_1
103 | - mistune=0.8.3=py_0
104 | - more-itertools=4.1.0=py_0
105 | - msgpack-python=0.5.6=py36_0
106 | - multipledispatch=0.5.0=py36_0
107 | - munch=2.3.1=py_0
108 | - nbconvert=5.3.1=py_1
109 | - nbformat=4.4.0=py36_0
110 | - ncurses=5.9=10
111 | - netcdf4=1.3.1=py36_2
112 | - networkx=2.1=py36_0
113 | - nodejs=9.11.0=0
114 | - notebook=5.4.1=py36_0
115 | - numpy=1.14.2=py36_blas_openblas_200
116 | - olefile=0.45.1=py36_0
117 | - openblas=0.2.20=7
118 | - openjpeg=2.3.0=2
119 | - packaging=17.1=py_0
120 | - pandas=0.22.0=py36_0
121 | - pandoc=2.1.3=0
122 | - pandocfilters=1.4.1=py36_0
123 | - parso=0.1.1=py_0
124 | - partd=0.3.8=py36_0
125 | - patsy=0.5.0=py36_0
126 | - pcre=8.41=1
127 | - pexpect=4.4.0=py36_0
128 | - pickleshare=0.7.4=py36_0
129 | - pillow=5.1.0=py36_0
130 | - pip=9.0.3=py36_0
131 | - pixman=0.34.0=1
132 | - pluggy=0.6.0=py_0
133 | - poppler=0.61.1=3
134 | - poppler-data=0.4.8=0
135 | - prompt_toolkit=1.0.15=py36_0
136 | - psutil=5.4.3=py36_0
137 | - psycopg2=2.7.4=py36_0
138 | - ptyprocess=0.5.2=py36_0
139 | - py=1.5.3=py_0
140 | - pygments=2.2.0=py36_0
141 | - pygpu=0.7.5=py36_0
142 | - pymc3=3.3=py36_0
143 | - pyparsing=2.2.0=py36_0
144 | - pyqt=5.6.0=py36_4
145 | - pysal=1.14.3=py36_0
146 | - pytest=3.5.0=py36_0
147 | - python=3.6.5=1
148 | - python-dateutil=2.7.2=py_0
149 | - python-snappy=0.5.2=py36_0
150 | - pytz=2018.4=py_0
151 | - pywavelets=0.5.2=py36_1
152 | - pyyaml=3.12=py36_1
153 | - pyzmq=17.0.0=py36_4
154 | - qt=5.6.2=7
155 | - readline=7.0=0
156 | - rtree=0.8.3=py36_0
157 | - scikit-image=0.13.1=py36_0
158 | - scikit-learn=0.19.1=py36_blas_openblas_201
159 | - scikit-plot=0.3.4=py36_0
160 | - scipy=1.0.1=py36_blas_openblas_200
161 | - seaborn=0.8.1=py36_0
162 | - send2trash=1.5.0=py_0
163 | - setuptools=39.0.1=py36_0
164 | - simplegeneric=0.8.1=py36_0
165 | - sip=4.18=py36_1
166 | - six=1.11.0=py36_1
167 | - snappy=1.1.7=1
168 | - sortedcontainers=1.5.9=py36_0
169 | - sqlalchemy=1.2.6=py36_0
170 | - sqlite=3.20.1=2
171 | - statsmodels=0.8.0=py36_0
172 | - tblib=1.3.2=py36_0
173 | - terminado=0.8.1=py36_0
174 | - testpath=0.3.1=py36_0
175 | - theano=1.0.1=py36_1
176 | - thrift=0.11.0=py36_0
177 | - tk=8.6.7=0
178 | - toolz=0.9.0=py_0
179 | - tornado=5.0.2=py36_0
180 | - tqdm=4.21.0=py_0
181 | - traitlets=4.3.2=py36_0
182 | - wcwidth=0.1.7=py36_0
183 | - webencodings=0.5=py36_0
184 | - wheel=0.31.0=py36_0
185 | - xarray=0.10.2=py36_0
186 | - xerces-c=3.2.0=0
187 | - xorg-libxau=1.0.8=3
188 | - xorg-libxdmcp=1.1.2=3
189 | - xz=5.2.3=0
190 | - yaml=0.1.7=0
191 | - zeromq=4.2.5=1
192 | - zict=0.1.3=py_0
193 | - zlib=1.2.11=0
194 | - asn1crypto=0.24.0=py36_0
195 | - ca-certificates=2018.03.07=0
196 | - cartopy=0.16.0=py36hf32a85a_0
197 | - certifi=2018.1.18=py36_0
198 | - cffi=1.11.5=py36h9745a5d_0
199 | - chardet=3.0.4=py36h0f667ec_1
200 | - geos=3.6.2=heeff764_2
201 | - idna=2.6=py36h82fb2a8_1
202 | - intel-openmp=2018.0.0=8
203 | - ipywidgets=7.2.0=py36_0
204 | - jupyter=1.0.0=py36_4
205 | - jupyter_console=5.2.0=py36he59e554_1
206 | - libgcc=7.2.0=h69d50b8_2
207 | - libgcc-ng=7.2.0=hdf63c60_3
208 | - libgfortran=3.0.0=1
209 | - libstdcxx-ng=7.2.0=hdf63c60_3
210 | - libxslt=1.1.32=h1312cb7_0
211 | - lxml=4.2.1=py36h23eabaa_0
212 | - mkl=2018.0.2=1
213 | - numba=0.36.2=np114py36hc6662d5_0
214 | - openssl=1.0.2o=h20670df_0
215 | - owslib=0.16.0=py36_0
216 | - pandas-profiling=1.4.1=py36_0
217 | - param=1.6.0=py36_0
218 | - proj4=4.9.3=hc8507d1_7
219 | - pycparser=2.18=py36hf9f622e_1
220 | - pyepsg=0.3.2=py36h1c26317_0
221 | - pyopenssl=17.5.0=py36h20ba746_0
222 | - pyproj=1.9.5.1=py36_0
223 | - pyshp=1.2.12=py36h04d6e4e_0
224 | - pysocks=1.6.8=py36_0
225 | - qtconsole=4.3.1=py36h8f73b5b_0
226 | - requests=2.18.4=py36he2e5f8d_1
227 | - shapely=1.6.4=py36h0c48222_0
228 | - urllib3=1.22=py36hbe7ace6_0
229 | - util-linux=2.21=0
230 | - widgetsnbextension=3.2.0=py36_0
231 | - geoviews=1.4.3=py36_0
232 | - holoviews=1.10.0=py_0
233 | - cuda90=1.0=h6433d27_0
234 | - pytorch=0.3.1=py36_cuda9.0.176_cudnn7.0.5_2
235 | - torchvision=0.2.0=py36h17b6947_1
236 | - pip:
237 | - holoext==0.0.3
238 | - jupyterlab-github==0.5.0
239 | - kaggle==1.1.0
240 | - torch==0.3.1.post2
241 | - version-information==1.0.3
242 | - yapf==0.21.0
243 | prefix: /home/abanihirwe/opt/miniconda3/envs/dl
244 |
245 |
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/datasets-notebooks/robocall-complaints/profilereport.html:
--------------------------------------------------------------------------------
1 |
2 |
3 |
4 |
5 |
6 |
7 | Profile report
8 |
9 |
10 |
11 |
12 |
14 |
16 |
17 |
42 |
43 |
44 |
45 |
46 |
47 |
260 |
261 |
262 |
265 |
266 |
267 |
Dataset info
268 |
269 |
270 |
271 | | Number of variables |
272 | 16 |
273 |
274 |
275 | | Number of observations |
276 | 99543 |
277 |
278 |
279 | | Total Missing (%) |
280 | 0.0% |
281 |
282 |
283 | | Total size in memory |
284 | 12.2 MiB |
285 |
286 |
287 | | Average record size in memory |
288 | 128.0 B |
289 |
290 |
291 |
292 |
293 |
294 |
Variables types
295 |
296 |
297 |
298 | | Numeric |
299 | 2 |
300 |
301 |
302 | | Categorical |
303 | 13 |
304 |
305 |
306 | | Boolean |
307 | 0 |
308 |
309 |
310 | | Date |
311 | 0 |
312 |
313 |
314 | | Text (Unique) |
315 | 0 |
316 |
317 |
318 | | Rejected |
319 | 1 |
320 |
321 |
322 | | Unsupported |
323 | 0 |
324 |
325 |
326 |
327 |
328 |
329 |
330 |
Warnings
331 |
332 |
333 |
334 |
337 |
338 |
339 |
Advertiser Business Number
340 | Categorical
341 |
342 |
343 |
344 |
345 | | Distinct count |
346 | 51878 |
347 |
348 |
349 | | Unique (%) |
350 | 52.1% |
351 |
352 |
353 | | Missing (%) |
354 | 0.0% |
355 |
356 |
357 | | Missing (n) |
358 | 0 |
359 |
360 |
361 |
362 |
363 |
364 |
365 | | None |
366 |
367 |
369 | 22265
370 |
371 |
372 | |
373 |
374 | | 000-000-0000 |
375 |
376 |
378 |
379 |
380 | 770
381 | |
382 |
383 | | 555-555-5555 |
384 |
385 |
387 |
388 |
389 | 365
390 | |
391 |
392 | | Other values (51875) |
393 |
394 |
396 | 76143
397 |
398 |
399 | |
400 |
401 |
402 |
403 |
409 |
500 |
501 |
502 |
Caller ID Number
503 | Categorical
504 |
505 |
506 |
507 |
508 | | Distinct count |
509 | 56973 |
510 |
511 |
512 | | Unique (%) |
513 | 57.2% |
514 |
515 |
516 | | Missing (%) |
517 | 0.0% |
518 |
519 |
520 | | Missing (n) |
521 | 0 |
522 |
523 |
524 |
525 |
526 |
527 |
528 | | None |
529 |
530 |
532 |
533 |
534 | 16546
535 | |
536 |
537 | | 213-141-5163 |
538 |
539 |
541 |
542 |
543 | 145
544 | |
545 |
546 | | 000-000-0000 |
547 |
548 |
550 |
551 |
552 | 121
553 | |
554 |
555 | | Other values (56970) |
556 |
557 |
559 | 82731
560 |
561 |
562 | |
563 |
564 |
565 |
566 |
572 |
663 |
664 |
665 |
City
666 | Categorical
667 |
668 |
669 |
670 |
671 | | Distinct count |
672 | 9751 |
673 |
674 |
675 | | Unique (%) |
676 | 9.8% |
677 |
678 |
679 | | Missing (%) |
680 | 0.0% |
681 |
682 |
683 | | Missing (n) |
684 | 0 |
685 |
686 |
687 |
688 |
689 |
690 |
691 | | Phoenix |
692 |
693 |
695 |
696 |
697 | 682
698 | |
699 |
700 | | Chicago |
701 |
702 |
704 |
705 |
706 | 670
707 | |
708 |
709 | | Houston |
710 |
711 |
713 |
714 |
715 | 663
716 | |
717 |
718 | | Other values (9748) |
719 |
720 |
722 | 97528
723 |
724 |
725 | |
726 |
727 |
728 |
729 |
735 |
826 |
827 |
828 |
Date of Issue
829 | Categorical
830 |
831 |
832 |
833 |
834 | | Distinct count |
835 | 1207 |
836 |
837 |
838 | | Unique (%) |
839 | 1.2% |
840 |
841 |
842 | | Missing (%) |
843 | 0.0% |
844 |
845 |
846 | | Missing (n) |
847 | 0 |
848 |
849 |
850 |
851 |
852 |
853 |
854 | | 08/29/2017 |
855 |
856 |
858 |
859 |
860 | 964
861 | |
862 |
863 | | 08/16/2017 |
864 |
865 |
867 |
868 |
869 | 958
870 | |
871 |
872 | | 08/23/2017 |
873 |
874 |
876 |
877 |
878 | 931
879 | |
880 |
881 | | Other values (1204) |
882 |
883 |
885 | 96690
886 |
887 |
888 | |
889 |
890 |
891 |
892 |
898 |
989 |
990 |
991 |
Form
992 | Constant
993 |
994 |
995 |
This variable is constant and should be ignored for analysis
996 |
997 |
998 |
999 |
1000 | | Constant value |
1001 | Phone |
1002 |
1003 |
1004 |
1005 |
1006 |
1007 |
Issue
1008 | Categorical
1009 |
1010 |
1011 |
1012 |
1013 | | Distinct count |
1014 | 3 |
1015 |
1016 |
1017 | | Unique (%) |
1018 | 0.0% |
1019 |
1020 |
1021 | | Missing (%) |
1022 | 0.0% |
1023 |
1024 |
1025 | | Missing (n) |
1026 | 0 |
1027 |
1028 |
1029 |
1030 |
1031 |
1032 |
1033 | | Unwanted Calls |
1034 |
1035 |
1037 | 54831
1038 |
1039 |
1040 | |
1041 |
1042 | | Telemarketing (including do not call and spoofing) |
1043 |
1044 |
1046 | 27417
1047 |
1048 |
1049 | |
1050 |
1051 | | Robocalls |
1052 |
1053 |
1055 | 17295
1056 |
1057 |
1058 | |
1059 |
1060 |
1061 |
1062 |
1068 |
1103 |
1104 |
1105 |
Location (Center point of the Zip Code)
1106 | Categorical
1107 |
1108 |
1109 |
1110 |
1111 | | Distinct count |
1112 | 19859 |
1113 |
1114 |
1115 | | Unique (%) |
1116 | 20.0% |
1117 |
1118 |
1119 | | Missing (%) |
1120 | 0.0% |
1121 |
1122 |
1123 | | Missing (n) |
1124 | 0 |
1125 |
1126 |
1127 |
1128 |
1129 |
1130 |
1131 | | CT 06880
1132 | (41.143865, -73.348008) |
1133 |
1134 |
1136 |
1137 |
1138 | 370
1139 | |
1140 |
1141 | | IA 52240
1142 | (41.646191, -91.509342) |
1143 |
1144 |
1146 |
1147 |
1148 | 221
1149 | |
1150 |
1151 | | CT 06053-1605
1152 | (41.695699, -72.796842) |
1153 |
1154 |
1156 |
1157 |
1158 | 212
1159 | |
1160 |
1161 | | Other values (19856) |
1162 |
1163 |
1165 | 98740
1166 |
1167 |
1168 | |
1169 |
1170 |
1171 |
1172 |
1178 |
1279 |
1280 |
1281 |
Method
1282 | Categorical
1283 |
1284 |
1285 |
1286 |
1287 | | Distinct count |
1288 | 3 |
1289 |
1290 |
1291 | | Unique (%) |
1292 | 0.0% |
1293 |
1294 |
1295 | | Missing (%) |
1296 | 0.0% |
1297 |
1298 |
1299 | | Missing (n) |
1300 | 0 |
1301 |
1302 |
1303 |
1304 |
1305 |
1306 |
1307 | | Wireless (cell phone/other mobile device) |
1308 |
1309 |
1311 | 58137
1312 |
1313 |
1314 | |
1315 |
1316 | | Wired |
1317 |
1318 |
1320 | 33366
1321 |
1322 |
1323 | |
1324 |
1325 | | Internet (VOIP) |
1326 |
1327 |
1329 |
1330 |
1331 | 8040
1332 | |
1333 |
1334 |
1335 |
1336 |
1342 |
1377 |
1378 |
1379 |
State
1380 | Categorical
1381 |
1382 |
1383 |
1384 |
1385 | | Distinct count |
1386 | 55 |
1387 |
1388 |
1389 | | Unique (%) |
1390 | 0.1% |
1391 |
1392 |
1393 | | Missing (%) |
1394 | 0.0% |
1395 |
1396 |
1397 | | Missing (n) |
1398 | 0 |
1399 |
1400 |
1401 |
1402 |
1403 |
1404 |
1405 | | CA |
1406 |
1407 |
1409 |
1410 |
1411 | 12212
1412 | |
1413 |
1414 | | TX |
1415 |
1416 |
1418 |
1419 |
1420 | 6784
1421 | |
1422 |
1423 | | FL |
1424 |
1425 |
1427 |
1428 |
1429 | 6529
1430 | |
1431 |
1432 | | Other values (52) |
1433 |
1434 |
1436 | 74018
1437 |
1438 |
1439 | |
1440 |
1441 |
1442 |
1443 |
1449 |
1540 |
1541 |
1542 |
Ticket Created
1543 | Categorical
1544 |
1545 |
1546 |
1547 |
1548 | | Distinct count |
1549 | 99050 |
1550 |
1551 |
1552 | | Unique (%) |
1553 | 99.5% |
1554 |
1555 |
1556 | | Missing (%) |
1557 | 0.0% |
1558 |
1559 |
1560 | | Missing (n) |
1561 | 0 |
1562 |
1563 |
1564 |
1565 |
1566 |
1567 |
1568 | | 07/24/2017 08:01:22 PM +0000 |
1569 |
1570 |
1572 |
1573 |
1574 | 3
1575 | |
1576 |
1577 | | 08/03/2017 06:56:17 PM +0000 |
1578 |
1579 |
1581 |
1582 |
1583 | 3
1584 | |
1585 |
1586 | | 08/22/2017 06:40:26 PM +0000 |
1587 |
1588 |
1590 |
1591 |
1592 | 3
1593 | |
1594 |
1595 | | Other values (99047) |
1596 |
1597 |
1599 | 99534
1600 |
1601 |
1602 | |
1603 |
1604 |
1605 |
1606 |
1612 |
1703 |
1704 |
1705 |
Ticket ID
1706 | Numeric
1707 |
1708 |
1709 |
1710 |
1711 |
1712 |
1713 | | Distinct count |
1714 | 99543 |
1715 |
1716 |
1717 | | Unique (%) |
1718 | 100.0% |
1719 |
1720 |
1721 | | Missing (%) |
1722 | 0.0% |
1723 |
1724 |
1725 | | Missing (n) |
1726 | 0 |
1727 |
1728 |
1729 | | Infinite (%) |
1730 | 0.0% |
1731 |
1732 |
1733 | | Infinite (n) |
1734 | 0 |
1735 |
1736 |
1737 |
1738 |
1739 |
1740 |
1741 |
1742 |
1743 | | Mean |
1744 | 1302800 |
1745 |
1746 |
1747 | | Minimum |
1748 | 537 |
1749 |
1750 |
1751 | | Maximum |
1752 | 1919007 |
1753 |
1754 |
1755 | | Zeros (%) |
1756 | 0.0% |
1757 |
1758 |
1759 |
1760 |
1761 |
1762 |
1763 |

1764 |
1765 |
1766 |
1772 |
1773 |
1785 |
1786 |
1787 |
1788 |
1789 |
Quantile statistics
1790 |
1791 |
1792 | | Minimum |
1793 | 537 |
1794 |
1795 |
1796 | | 5-th percentile |
1797 | 181920 |
1798 |
1799 |
1800 | | Q1 |
1801 | 780340 |
1802 |
1803 |
1804 | | Median |
1805 | 1707000 |
1806 |
1807 |
1808 | | Q3 |
1809 | 1821200 |
1810 |
1811 |
1812 | | 95-th percentile |
1813 | 1898400 |
1814 |
1815 |
1816 | | Maximum |
1817 | 1919007 |
1818 |
1819 |
1820 | | Range |
1821 | 1918470 |
1822 |
1823 |
1824 | | Interquartile range |
1825 | 1040900 |
1826 |
1827 |
1828 |
1829 |
1830 |
Descriptive statistics
1831 |
1832 |
1833 | | Standard deviation |
1834 | 610570 |
1835 |
1836 |
1837 | | Coef of variation |
1838 | 0.46868 |
1839 |
1840 |
1841 | | Kurtosis |
1842 | -1.1136 |
1843 |
1844 |
1845 | | Mean |
1846 | 1302800 |
1847 |
1848 |
1849 | | MAD |
1850 | 554550 |
1851 |
1852 |
1853 | | Skewness |
1854 | -0.63483 |
1855 |
1856 |
1857 | | Sum |
1858 | 129680285912 |
1859 |
1860 |
1861 | | Variance |
1862 | 372800000000 |
1863 |
1864 |
1865 | | Memory size |
1866 | 777.8 KiB |
1867 |
1868 |
1869 |
1870 |
1871 |
1872 |

1873 |
1874 |
1875 |
1876 |
1877 |
1878 |
1879 | | Value |
1880 | Count |
1881 | Frequency (%) |
1882 | |
1883 |
1884 |
1885 |
1886 | | 1837055 |
1887 | 1 |
1888 | 0.0% |
1889 |
1890 |
1891 | |
1892 |
1893 | | 1732119 |
1894 | 1 |
1895 | 0.0% |
1896 |
1897 |
1898 | |
1899 |
1900 | | 1857100 |
1901 | 1 |
1902 | 0.0% |
1903 |
1904 |
1905 | |
1906 |
1907 | | 1121014 |
1908 | 1 |
1909 | 0.0% |
1910 |
1911 |
1912 | |
1913 |
1914 | | 1892228 |
1915 | 1 |
1916 | 0.0% |
1917 |
1918 |
1919 | |
1920 |
1921 | | 1779066 |
1922 | 1 |
1923 | 0.0% |
1924 |
1925 |
1926 | |
1927 |
1928 | | 621306 |
1929 | 1 |
1930 | 0.0% |
1931 |
1932 |
1933 | |
1934 |
1935 | | 619259 |
1936 | 1 |
1937 | 0.0% |
1938 |
1939 |
1940 | |
1941 |
1942 | | 1898664 |
1943 | 1 |
1944 | 0.0% |
1945 |
1946 |
1947 | |
1948 |
1949 | | 875262 |
1950 | 1 |
1951 | 0.0% |
1952 |
1953 |
1954 | |
1955 |
1956 | | Other values (99533) |
1957 | 99533 |
1958 | 100.0% |
1959 |
1960 |
1961 | |
1962 |
1963 |
1964 |
1965 |
1966 |
Minimum 5 values
1967 |
1968 |
1969 |
1970 |
1971 | | Value |
1972 | Count |
1973 | Frequency (%) |
1974 | |
1975 |
1976 |
1977 |
1978 | | 537 |
1979 | 1 |
1980 | 0.0% |
1981 |
1982 |
1983 | |
1984 |
1985 | | 579 |
1986 | 1 |
1987 | 0.0% |
1988 |
1989 |
1990 | |
1991 |
1992 | | 585 |
1993 | 1 |
1994 | 0.0% |
1995 |
1996 |
1997 | |
1998 |
1999 | | 636 |
2000 | 1 |
2001 | 0.0% |
2002 |
2003 |
2004 | |
2005 |
2006 | | 680 |
2007 | 1 |
2008 | 0.0% |
2009 |
2010 |
2011 | |
2012 |
2013 |
2014 |
Maximum 5 values
2015 |
2016 |
2017 |
2018 |
2019 | | Value |
2020 | Count |
2021 | Frequency (%) |
2022 | |
2023 |
2024 |
2025 |
2026 | | 1918979 |
2027 | 1 |
2028 | 0.0% |
2029 |
2030 |
2031 | |
2032 |
2033 | | 1918984 |
2034 | 1 |
2035 | 0.0% |
2036 |
2037 |
2038 | |
2039 |
2040 | | 1918995 |
2041 | 1 |
2042 | 0.0% |
2043 |
2044 |
2045 | |
2046 |
2047 | | 1919004 |
2048 | 1 |
2049 | 0.0% |
2050 |
2051 |
2052 | |
2053 |
2054 | | 1919007 |
2055 | 1 |
2056 | 0.0% |
2057 |
2058 |
2059 | |
2060 |
2061 |
2062 |
2063 |
2064 |
2065 |
2066 |
2067 |
Time of Issue
2068 | Categorical
2069 |
2070 |
2071 |
2072 |
2073 | | Distinct count |
2074 | 6048 |
2075 |
2076 |
2077 | | Unique (%) |
2078 | 6.1% |
2079 |
2080 |
2081 | | Missing (%) |
2082 | 0.0% |
2083 |
2084 |
2085 | | Missing (n) |
2086 | 0 |
2087 |
2088 |
2089 |
2090 |
2091 |
2092 |
2093 | | 1:00 pm |
2094 |
2095 |
2097 |
2098 |
2099 | 1433
2100 | |
2101 |
2102 | | 10:00 am |
2103 |
2104 |
2106 |
2107 |
2108 | 1203
2109 | |
2110 |
2111 | | 11:00 am |
2112 |
2113 |
2115 |
2116 |
2117 | 1086
2118 | |
2119 |
2120 | | Other values (6045) |
2121 |
2122 |
2124 | 95821
2125 |
2126 |
2127 | |
2128 |
2129 |
2130 |
2131 |
2137 |
2228 |
2229 |
2230 |
Type of Call or Messge
2231 | Categorical
2232 |
2233 |
2234 |
2235 |
2236 | | Distinct count |
2237 | 6 |
2238 |
2239 |
2240 | | Unique (%) |
2241 | 0.0% |
2242 |
2243 |
2244 | | Missing (%) |
2245 | 0.0% |
2246 |
2247 |
2248 | | Missing (n) |
2249 | 0 |
2250 |
2251 |
2252 |
2253 |
2254 |
2255 |
2256 | | Prerecorded Voice |
2257 |
2258 |
2260 | 52032
2261 |
2262 |
2263 | |
2264 |
2265 | | Live Voice |
2266 |
2267 |
2269 | 29201
2270 |
2271 |
2272 | |
2273 |
2274 | | Abandoned Calls |
2275 |
2276 |
2278 | 14253
2279 |
2280 |
2281 | |
2282 |
2283 | | Other values (3) |
2284 |
2285 |
2287 |
2288 |
2289 | 4057
2290 | |
2291 |
2292 |
2293 |
2294 |
2300 |
2356 |
2357 |
2358 |
Zip
2359 | Categorical
2360 |
2361 |
2362 |
2363 |
2364 | | Distinct count |
2365 | 16554 |
2366 |
2367 |
2368 | | Unique (%) |
2369 | 16.6% |
2370 |
2371 |
2372 | | Missing (%) |
2373 | 0.0% |
2374 |
2375 |
2376 | | Missing (n) |
2377 | 0 |
2378 |
2379 |
2380 |
2381 |
2382 |
2383 |
2384 | | 06880 |
2385 |
2386 |
2388 |
2389 |
2390 | 370
2391 | |
2392 |
2393 | | 40601 |
2394 |
2395 |
2397 |
2398 |
2399 | 237
2400 | |
2401 |
2402 | | 06053 |
2403 |
2404 |
2406 |
2407 |
2408 | 225
2409 | |
2410 |
2411 | | Other values (16551) |
2412 |
2413 |
2415 | 98711
2416 |
2417 |
2418 | |
2419 |
2420 |
2421 |
2422 |
2428 |
2519 |
2520 |
2521 |
index
2522 | Numeric
2523 |
2524 |
2525 |
2526 |
2527 |
2528 |
2529 | | Distinct count |
2530 | 99543 |
2531 |
2532 |
2533 | | Unique (%) |
2534 | 100.0% |
2535 |
2536 |
2537 | | Missing (%) |
2538 | 0.0% |
2539 |
2540 |
2541 | | Missing (n) |
2542 | 0 |
2543 |
2544 |
2545 | | Infinite (%) |
2546 | 0.0% |
2547 |
2548 |
2549 | | Infinite (n) |
2550 | 0 |
2551 |
2552 |
2553 |
2554 |
2555 |
2556 |
2557 |
2558 |
2559 | | Mean |
2560 | 610290 |
2561 |
2562 |
2563 | | Minimum |
2564 | 1 |
2565 |
2566 |
2567 | | Maximum |
2568 | 943109 |
2569 |
2570 |
2571 | | Zeros (%) |
2572 | 0.0% |
2573 |
2574 |
2575 |
2576 |
2577 |
2578 |
2579 |

2580 |
2581 |
2582 |
2588 |
2589 |
2601 |
2602 |
2603 |
2604 |
2605 |
Quantile statistics
2606 |
2607 |
2608 | | Minimum |
2609 | 1 |
2610 |
2611 |
2612 | | 5-th percentile |
2613 | 62299 |
2614 |
2615 |
2616 | | Q1 |
2617 | 360170 |
2618 |
2619 |
2620 | | Median |
2621 | 708780 |
2622 |
2623 |
2624 | | Q3 |
2625 | 888740 |
2626 |
2627 |
2628 | | 95-th percentile |
2629 | 935160 |
2630 |
2631 |
2632 | | Maximum |
2633 | 943109 |
2634 |
2635 |
2636 | | Range |
2637 | 943108 |
2638 |
2639 |
2640 | | Interquartile range |
2641 | 528570 |
2642 |
2643 |
2644 |
2645 |
2646 |
Descriptive statistics
2647 |
2648 |
2649 | | Standard deviation |
2650 | 300000 |
2651 |
2652 |
2653 | | Coef of variation |
2654 | 0.49157 |
2655 |
2656 |
2657 | | Kurtosis |
2658 | -1.0474 |
2659 |
2660 |
2661 | | Mean |
2662 | 610290 |
2663 |
2664 |
2665 | | MAD |
2666 | 262760 |
2667 |
2668 |
2669 | | Skewness |
2670 | -0.5892 |
2671 |
2672 |
2673 | | Sum |
2674 | 60750388843 |
2675 |
2676 |
2677 | | Variance |
2678 | 90001000000 |
2679 |
2680 |
2681 | | Memory size |
2682 | 777.8 KiB |
2683 |
2684 |
2685 |
2686 |
2687 |
2688 |

2689 |
2690 |
2691 |
2692 |
2693 |
2694 |
2695 | | Value |
2696 | Count |
2697 | Frequency (%) |
2698 | |
2699 |
2700 |
2701 |
2702 | | 792573 |
2703 | 1 |
2704 | 0.0% |
2705 |
2706 |
2707 | |
2708 |
2709 | | 709513 |
2710 | 1 |
2711 | 0.0% |
2712 |
2713 |
2714 | |
2715 |
2716 | | 808647 |
2717 | 1 |
2718 | 0.0% |
2719 |
2720 |
2721 | |
2722 |
2723 | | 909993 |
2724 | 1 |
2725 | 0.0% |
2726 |
2727 |
2728 | |
2729 |
2730 | | 804767 |
2731 | 1 |
2732 | 0.0% |
2733 |
2734 |
2735 | |
2736 |
2737 | | 641708 |
2738 | 1 |
2739 | 0.0% |
2740 |
2741 |
2742 | |
2743 |
2744 | | 776878 |
2745 | 1 |
2746 | 0.0% |
2747 |
2748 |
2749 | |
2750 |
2751 | | 905903 |
2752 | 1 |
2753 | 0.0% |
2754 |
2755 |
2756 | |
2757 |
2758 | | 942521 |
2759 | 1 |
2760 | 0.0% |
2761 |
2762 |
2763 | |
2764 |
2765 | | 891405 |
2766 | 1 |
2767 | 0.0% |
2768 |
2769 |
2770 | |
2771 |
2772 | | Other values (99533) |
2773 | 99533 |
2774 | 100.0% |
2775 |
2776 |
2777 | |
2778 |
2779 |
2780 |
2781 |
2782 |
Minimum 5 values
2783 |
2784 |
2785 |
2786 |
2787 | | Value |
2788 | Count |
2789 | Frequency (%) |
2790 | |
2791 |
2792 |
2793 |
2794 | | 1 |
2795 | 1 |
2796 | 0.0% |
2797 |
2798 |
2799 | |
2800 |
2801 | | 2 |
2802 | 1 |
2803 | 0.0% |
2804 |
2805 |
2806 | |
2807 |
2808 | | 6 |
2809 | 1 |
2810 | 0.0% |
2811 |
2812 |
2813 | |
2814 |
2815 | | 20 |
2816 | 1 |
2817 | 0.0% |
2818 |
2819 |
2820 | |
2821 |
2822 | | 36 |
2823 | 1 |
2824 | 0.0% |
2825 |
2826 |
2827 | |
2828 |
2829 |
2830 |
Maximum 5 values
2831 |
2832 |
2833 |
2834 |
2835 | | Value |
2836 | Count |
2837 | Frequency (%) |
2838 | |
2839 |
2840 |
2841 |
2842 | | 943100 |
2843 | 1 |
2844 | 0.0% |
2845 |
2846 |
2847 | |
2848 |
2849 | | 943101 |
2850 | 1 |
2851 | 0.0% |
2852 |
2853 |
2854 | |
2855 |
2856 | | 943102 |
2857 | 1 |
2858 | 0.0% |
2859 |
2860 |
2861 | |
2862 |
2863 | | 943106 |
2864 | 1 |
2865 | 0.0% |
2866 |
2867 |
2868 | |
2869 |
2870 | | 943109 |
2871 | 1 |
2872 | 0.0% |
2873 |
2874 |
2875 | |
2876 |
2877 |
2878 |
2879 |
2880 |
2881 |
2882 |
2883 |
location
2884 | Categorical
2885 |
2886 |
2887 |
2888 |
2889 | | Distinct count |
2890 | 18443 |
2891 |
2892 |
2893 | | Unique (%) |
2894 | 18.5% |
2895 |
2896 |
2897 | | Missing (%) |
2898 | 0.0% |
2899 |
2900 |
2901 | | Missing (n) |
2902 | 0 |
2903 |
2904 |
2905 |
2906 |
2907 |
2908 |
2909 | | 41.143865, -73.348008 |
2910 |
2911 |
2913 |
2914 |
2915 | 370
2916 | |
2917 |
2918 | | 41.646191, -91.509342 |
2919 |
2920 |
2922 |
2923 |
2924 | 221
2925 | |
2926 |
2927 | | 41.695699, -72.796842 |
2928 |
2929 |
2931 |
2932 |
2933 | 212
2934 | |
2935 |
2936 | | Other values (18440) |
2937 |
2938 |
2940 | 98740
2941 |
2942 |
2943 | |
2944 |
2945 |
2946 |
2947 |
2953 |
3044 |
3045 |
3048 |
3049 |

3050 |

3051 |
3052 |
3055 |
3056 |
3057 |
3058 |
3059 |
3060 | |
3061 | Ticket ID |
3062 | Ticket Created |
3063 | Date of Issue |
3064 | Time of Issue |
3065 | Form |
3066 | Method |
3067 | Issue |
3068 | Caller ID Number |
3069 | Type of Call or Messge |
3070 | Advertiser Business Number |
3071 | City |
3072 | State |
3073 | Zip |
3074 | Location (Center point of the Zip Code) |
3075 | location |
3076 |
3077 |
3078 |
3079 |
3080 | | 1 |
3081 | 1000319 |
3082 | 05/25/2016 12:51:35 PM +0000 |
3083 | 03/07/2016 |
3084 | 12:00 pm |
3085 | Phone |
3086 | Wired |
3087 | Telemarketing (including do not call and spoof... |
3088 | 619-840-7262 |
3089 | Live Voice |
3090 | 619-840-7262 |
3091 | San Marcos |
3092 | CA |
3093 | 92078 |
3094 | CA 92078\n(33.122635, -117.190612) |
3095 | 33.122635, -117.190612 |
3096 |
3097 |
3098 | | 2 |
3099 | 1000322 |
3100 | 05/25/2016 12:56:54 PM +0000 |
3101 | 05/24/2016 |
3102 | 8:08 PM |
3103 | Phone |
3104 | Wireless (cell phone/other mobile device) |
3105 | Telemarketing (including do not call and spoof... |
3106 | 626-691-9090 |
3107 | Live Voice |
3108 | 626-691-9090 |
3109 | Wyckoff |
3110 | NJ |
3111 | 07481 |
3112 | NJ 07481\n(40.998076, -74.167269) |
3113 | 40.998076, -74.167269 |
3114 |
3115 |
3116 | | 6 |
3117 | 1000330 |
3118 | 05/25/2016 01:10:06 PM +0000 |
3119 | 03/14/2016 |
3120 | 11:00 am |
3121 | Phone |
3122 | Wired |
3123 | Telemarketing (including do not call and spoof... |
3124 | 484-938-8231 |
3125 | Live Voice |
3126 | 484-938-8231 |
3127 | Allentown |
3128 | PA |
3129 | 18104 |
3130 | PA 18104\n(40.60276, -75.537329) |
3131 | 40.60276, -75.537329 |
3132 |
3133 |
3134 | | 20 |
3135 | 1000398 |
3136 | 05/25/2016 02:21:55 PM +0000 |
3137 | 05/23/2016 |
3138 | 7:15 am |
3139 | Phone |
3140 | Wired |
3141 | Telemarketing (including do not call and spoof... |
3142 | 857-240-6699 |
3143 | Live Voice |
3144 | 857-240-6699 |
3145 | Havertown |
3146 | PA |
3147 | 19083 |
3148 | PA 19083\n(39.977505, -75.31077) |
3149 | 39.977505, -75.31077 |
3150 |
3151 |
3152 | | 36 |
3153 | 1000460 |
3154 | 05/25/2016 03:00:07 PM +0000 |
3155 | 05/25/2016 |
3156 | 9:49 A.M. |
3157 | Phone |
3158 | Wired |
3159 | Robocalls |
3160 | 206-823-3345 |
3161 | Prerecorded Voice |
3162 | 206-823-3082 |
3163 | Lock Haven |
3164 | PA |
3165 | 17745 |
3166 | PA 17745\n(41.200712, -77.442936) |
3167 | 41.200712, -77.442936 |
3168 |
3169 |
3170 |
3171 |
3172 |
3173 |
3174 |
3175 |
--------------------------------------------------------------------------------