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shapely/constructive.py:180: RuntimeWarning: invalid value encountered in buffer return lib.buffer(
ALL software version info
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Software Version Info
downloaded ipynb from here "https://hvplot.holoviz.org/reference/geopandas/polygons.html"
# Name Version Build Channel
appnope 0.1.4 pyhd8ed1ab_1 conda-forge
arrow-cpp 19.0.0 h0b7d223_2
asttokens 3.0.0 pyhd8ed1ab_1 conda-forge
aws-c-auth 0.6.19 h80987f9_0
aws-c-cal 0.5.20 h80987f9_0
aws-c-common 0.8.5 h80987f9_0
aws-c-compression 0.2.16 h80987f9_0
aws-c-event-stream 0.2.15 h313beb8_0
aws-c-http 0.6.25 h80987f9_0
aws-c-io 0.13.10 h80987f9_0
aws-c-mqtt 0.7.13 h80987f9_0
aws-c-s3 0.1.51 h80987f9_0
aws-c-sdkutils 0.1.6 h80987f9_0
aws-checksums 0.1.13 h80987f9_0
aws-crt-cpp 0.18.16 h313beb8_0
aws-sdk-cpp 1.11.212 hdd7fb2f_0
blas 1.0 openblas
bleach 6.2.0 py313hca03da5_0
blinker 1.9.0 pypi_0 pypi
blosc 1.21.3 h313beb8_0
bokeh 3.7.3 py_0 bokeh
boost-cpp 1.82.0 h48ca7d4_2
bottleneck 1.4.2 py313ha35b7ea_0
branca 0.6.0 py313hca03da5_0
brotli-python 1.0.9 py313h313beb8_9
bzip2 1.0.8 h80987f9_6
c-ares 1.19.1 h80987f9_0
ca-certificates 2025.4.26 hbd8a1cb_0 conda-forge
cairo 1.16.0 h302bd0f_5
cartopy 0.24.1 pypi_0 pypi
certifi 2025.4.26 py313hca03da5_0
cfitsio 3.470 h7f6438f_7
charset-normalizer 3.3.2 pyhd3eb1b0_0
click 8.2.0 pypi_0 pypi
colorcet 3.1.0 py313hca03da5_0
comm 0.2.2 pyhd8ed1ab_1 conda-forge
contourpy 1.3.1 py313h48ca7d4_0
cramjam 2.9.1 py313h00184e3_0
cycler 0.11.0 pyhd3eb1b0_0
cyrus-sasl 2.1.28 h9131b1a_1
dash 3.0.4 pypi_0 pypi
debugpy 1.8.11 py313h313beb8_0
decorator 5.2.1 pyhd8ed1ab_0 conda-forge
et_xmlfile 1.1.0 py313hca03da5_1
exceptiongroup 1.3.0 pyhd8ed1ab_0 conda-forge
executing 2.2.0 pyhd8ed1ab_0 conda-forge
expat 2.7.1 h313beb8_0
fastparquet 2024.11.0 py313ha35b7ea_1
flask 3.0.3 pypi_0 pypi
folium 0.14.0 py313hca03da5_0
fontconfig 2.14.1 h6402c1e_3
fonttools 4.55.3 py313h80987f9_0
freetype 2.13.3 h47d26ad_0
freexl 2.0.0 ha3de405_0
fsspec 2025.3.2 py313h7eb115d_0
geodatasets 2024.8.0 pypi_0 pypi
geopandas 1.0.1 py313hca03da5_0
geopandas-base 1.0.1 py313hca03da5_0
geos 3.10.6 h313beb8_0
geotiff 1.7.0 hcec61be_4
geoviews 1.14.0 pypi_0 pypi
gettext 0.21.0 hbdbcc25_2
gflags 2.2.2 h313beb8_1
giflib 5.2.2 h80987f9_0
glib 2.78.4 h313beb8_0
glib-tools 2.78.4 h313beb8_0
glog 0.5.0 h313beb8_1
hdf4 4.2.13 h5e329fb_3
hdf5 1.14.5 hd77251f_2
holoviews 1.20.2 py313hca03da5_0
hvplot 0.11.3 py313hca03da5_0
icu 73.1 h313beb8_0
idna 3.7 py313hca03da5_0
importlib-metadata 8.7.0 pypi_0 pypi
ipykernel 6.29.5 pyh57ce528_0 conda-forge
ipython 8.36.0 pyh907856f_0 conda-forge
ipywidgets 8.1.5 py313hca03da5_0
itsdangerous 2.2.0 pypi_0 pypi
jedi 0.19.2 pyhd8ed1ab_1 conda-forge
jinja2 3.1.6 pypi_0 pypi
joblib 1.4.2 py313hca03da5_0
jpeg 9e h80987f9_3
json-c 0.16 h1a28f6b_0
jupyter_bokeh 4.0.5 py313h80987f9_0
jupyter_client 8.6.3 pyhd8ed1ab_1 conda-forge
jupyter_core 5.7.2 pyh31011fe_1 conda-forge
jupyterlab_widgets 3.0.13 py313hca03da5_0
kealib 1.5.0 h3444380_2
kiwisolver 1.4.8 py313h313beb8_0
krb5 1.20.1 hf3e1bf2_1
lcms2 2.16 he26ebf3_1
lerc 4.0.0 h313beb8_0
libabseil 20250127.0 cxx17_h313beb8_0
libboost 1.82.0 h0bc93f9_2
libbrotlicommon 1.0.9 h80987f9_9
libbrotlidec 1.0.9 h80987f9_9
libbrotlienc 1.0.9 h80987f9_9
libcurl 8.12.1 hde089ae_0
libcxx 14.0.6 h848a8c0_0
libdeflate 1.22 h80987f9_0
libedit 3.1.20230828 h80987f9_0
libev 4.33 h1a28f6b_1
libevent 2.1.12 h02f6b3c_1
libffi 3.4.4 hca03da5_1
libgdal 3.6.2 hb8790f9_10
libgfortran 5.0.0 11_3_0_hca03da5_28
libgfortran5 11.3.0 h009349e_28
libglib 2.78.4 h0a96307_0
libgrpc 1.71.0 h62f6fdd_0
libiconv 1.16 h80987f9_3
libkml 1.3.0 hc4d7c42_7
libmpdec 4.0.0 h80987f9_0
libnetcdf 4.8.1 h7d1a7d1_5
libnghttp2 1.57.0 h62f6fdd_0
libopenblas 0.3.29 hea593b9_0
libpng 1.6.39 h80987f9_0
libpq 17.4 h02f6b3c_0
libprotobuf 5.29.3 h9f9f828_0
libre2-11 2024.07.02 h313beb8_0
libsodium 1.0.18 h27ca646_1 conda-forge
libspatialite 5.1.0 h4e90699_2
libssh2 1.11.1 h3e2b118_0
libthrift 0.15.0 h73c2103_2
libtiff 4.7.0 h91aec0a_0
libwebp-base 1.3.2 h80987f9_1
libxml2 2.13.8 h0b34f26_0
libxslt 1.1.41 hf4d3faa_0
libzip 1.8.0 h62fee54_1
linkify-it-py 2.0.0 py313hca03da5_0
llvm-openmp 14.0.6 hc6e5704_0
lxml 5.3.0 py313h1d4350b_1
lz4-c 1.9.4 h313beb8_1
mapclassify 2.5.0 py313hca03da5_0
markdown 3.8 py313hca03da5_0
markdown-it-py 2.2.0 py313hca03da5_1
markupsafe 3.0.2 pypi_0 pypi
matplotlib 3.10.0 py313hca03da5_1
matplotlib-base 3.10.0 py313hb68df00_0
matplotlib-inline 0.1.7 pyhd8ed1ab_1 conda-forge
mdit-py-plugins 0.3.0 py313hca03da5_0
mdurl 0.1.0 py313hca03da5_0
minizip 4.0.3 ha89c15f_0
narwhals 1.39.1 pypi_0 pypi
ncurses 6.4 h313beb8_0
nest-asyncio 1.6.0 pypi_0 pypi
networkx 3.4.2 py313hca03da5_0
nspr 4.35 h313beb8_0
nss 3.89.1 h313beb8_0
numexpr 2.10.1 py313h5d9532f_0
numpy 2.2.5 py313hdcf7240_0
numpy-base 2.2.5 py313h9d8309b_0
ocw-project 0.1.0 dev_0 <develop>
openjpeg 2.5.2 hba36e21_1
openldap 2.6.4 he7ef289_0
openpyxl 3.1.5 py313h80987f9_1
openssl 3.5.0 h81ee809_1 conda-forge
orc 2.1.1 h55d209b_0
packaging 24.2 py313hca03da5_0
pandas 2.2.3 py313hcf29cfe_0
pandas-datareader 0.10.0 pyhd3eb1b0_0
panel 1.7.0 py313hca03da5_0
param 2.2.0 py313hca03da5_0
parso 0.8.4 pyhd8ed1ab_1 conda-forge
pcre2 10.42 hb066dcc_1
pexpect 4.9.0 pyhd8ed1ab_1 conda-forge
pickleshare 0.7.5 pyhd8ed1ab_1004 conda-forge
pillow 11.1.0 py313h41ba818_1
pip 25.1 pyhc872135_2
pixman 0.40.0 h1a28f6b_0
platformdirs 4.3.8 pyhe01879c_0 conda-forge
plotly 6.1.0 pypi_0 pypi
pooch 1.8.2 pypi_0 pypi
poppler 24.09.0 hb57d120_2
poppler-data 0.4.11 hca03da5_1
proj 9.3.1 hdced247_1
prompt-toolkit 3.0.51 pyha770c72_0 conda-forge
psutil 7.0.0 py313h90d716c_0 conda-forge
ptyprocess 0.7.0 pyhd8ed1ab_1 conda-forge
pure_eval 0.2.3 pyhd8ed1ab_1 conda-forge
pyarrow 19.0.0 py313h313beb8_1
pygments 2.19.1 pyhd8ed1ab_0 conda-forge
pyogrio 0.10.0 py313hcf39714_0
pyparsing 3.2.0 py313hca03da5_0
pyproj 3.6.1 py313hf165acc_1
pyshp 2.3.1 pypi_0 pypi
pysocks 1.7.1 py313hca03da5_0
python 3.13.2 h4862095_100_cp313
python-dateutil 2.9.0post0 py313hca03da5_2
python-tzdata 2025.2 pyhd3eb1b0_0
python_abi 3.13 0_cp313
pytz 2024.1 py313hca03da5_0
pyviz_comms 3.0.2 py313hca03da5_0
pyyaml 6.0.2 py313h80987f9_0
pyzmq 25.1.2 py313h313beb8_0
qhull 2020.2 h48ca7d4_2
re2 2024.07.02 h48ca7d4_0
readline 8.2 h1a28f6b_0
requests 2.32.3 py313hca03da5_1
retrying 1.3.4 pypi_0 pypi
scikit-learn 1.6.1 py313h313beb8_0
scipy 1.15.3 py313hd7edaaf_0
setuptools 72.1.0 py313hca03da5_0
shapely 2.0.6 py313hc1b91b6_0
six 1.17.0 py313hca03da5_0
snappy 1.2.1 h313beb8_0
sqlite 3.45.3 h80987f9_0
stack_data 0.6.3 pyhd8ed1ab_1 conda-forge
threadpoolctl 3.5.0 py313h7eb115d_0
tiledb 2.3.3 hb4a6b97_3
tk 8.6.14 h6ba3021_0
tornado 6.4.2 py313h80987f9_0
tqdm 4.67.1 py313h7eb115d_0
traitlets 5.14.3 pyhd8ed1ab_1 conda-forge
typing-extensions 4.12.2 py313hca03da5_0
typing_extensions 4.12.2 py313hca03da5_0
tzdata 2025b h04d1e81_0
uc-micro-py 1.0.1 py313hca03da5_0
uriparser 0.9.7 h80987f9_0
urllib3 2.3.0 py313hca03da5_0
utf8proc 2.6.1 h80987f9_1
wcwidth 0.2.13 pyhd8ed1ab_1 conda-forge
webencodings 0.5.1 py313hca03da5_2
werkzeug 3.0.6 pypi_0 pypi
wheel 0.45.1 py313hca03da5_0
widgetsnbextension 4.0.13 py313hca03da5_0
xerces-c 3.2.4 h313beb8_1
xlrd 2.0.1 pyhd3eb1b0_1
xyzservices 2022.9.0 py313hca03da5_1
xz 5.6.4 h80987f9_1
yaml 0.2.5 h1a28f6b_0
zeromq 4.3.5 h313beb8_0
zipp 3.21.0 pypi_0 pypi
zlib 1.2.13 h18a0788_1
zstd 1.5.6 hfb09047_0
Description of expected behavior and the observed behavior
/shapely/constructive.py:180: RuntimeWarning: invalid value encountered in buffer return lib.buffer(
=> received this error when running the notebook file from "https://hvplot.holoviz.org/reference/geopandas/polygons.html"
had the same error message with my project, maybe this is linked to installed versions?
Complete, minimal, self-contained example code that reproduces the issue
chicago.hvplot.polygons(
geo=True,
c=chicago.POP2010/chicago.to_crs('EPSG:32616').area,
clabel='pop density',
)
Stack traceback and/or browser JavaScript console output
Screenshots or screencasts of the bug in action
- [ ] I may be interested in making a pull request to address this
Hi, I was not able to reproduce your error:
import hvplot.pandas
import geodatasets
import geopandas as gpd
import numpy as np
chicago = gpd.read_file(geodatasets.get_path("geoda.chicago_commpop"))
chicago.hvplot.polygons(
geo=True,
c=chicago.POP2010/chicago.to_crs('EPSG:32616').area,
clabel='pop density',
)
Can you try to update to the latest versions of the following dependencies and try again?
Relevant Libraries
hvPlot: 0.11.4.dev45+g854e10b Geopandas: 1.1.1 Numpy: 2.2.6
