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Altair + Pandas Crashes Jupyter Lab
See original GitHub issueI am having some issues using Altair in Jupyter Lab.
When running a stock example off of the documentation page, I have no issues:
import altair as alt
from vega_datasets import data
cars = data.cars.url
print(cars)
chart = alt.Chart(cars).mark_point().encode(
x='Horsepower:Q',
y='Miles_per_Gallon:Q',
color='Origin:N',
)
chart
However, when I try a basic chart using my own data with Pandas, I crash Jupyter Lab
import pandas as pd
import altair as alt
df = pd.read_csv('FX_VOLUME_1537480100441.csv', index_col=0)
df.dropna(how='any', axis=0, inplace=True)
df.reset_index(drop=False, inplace=True)
d = df.loc[:, ['TRADE_DATE', 'EURO']]
d.shape
alt.Chart(d).mark_point().encode(
x='TRADE_DATE',
y='EURO'
)
For background, this is a time series with a single variable and is ~2500 observation in length.
I have a fresh Anaconda install. Let me know what other information I can provide…
# packages in environment at C:\Anaconda3:
#
# Name Version Build Channel
_ipyw_jlab_nb_ext_conf 0.1.0 py37_0
alabaster 0.7.11 py37_0
altair 2.2.2 <pip>
anaconda custom py37_0
anaconda-client 1.7.2 py37_0
anaconda-navigator 1.9.2 py37_0
anaconda-project 0.8.2 py37_0
appdirs 1.4.3 py37h28b3542_0
asn1crypto 0.24.0 py37_0
astroid 2.0.4 py37_0
astropy 3.0.4 py37hfa6e2cd_0
atomicwrites 1.2.1 py37_0
attrs 18.2.0 py37h28b3542_0
automat 0.7.0 py37_0
babel 2.6.0 py37_0
backcall 0.1.0 py37_0
backports 1.0 py37_1
backports.shutil_get_terminal_size 1.0.0 py37_2
beautifulsoup4 4.6.3 py37_0
bitarray 0.8.3 py37hfa6e2cd_0
bkcharts 0.2 py37_0
blas 1.0 mkl
blaze 0.11.3 py37_0
bleach 2.1.4 py37_0
blosc 1.14.4 he51fdeb_0
bokeh 0.13.0 py37_0
boto 2.49.0 py37_0
bottleneck 1.2.1 py37h452e1ab_1
bzip2 1.0.6 hfa6e2cd_5
ca-certificates 2018.03.07 0
certifi 2018.8.24 py37_1
cffi 1.11.5 py37h74b6da3_1
chardet 3.0.4 py37_1
click 6.7 py37_0
cloudpickle 0.5.6 py37_0
clyent 1.2.2 py37_1
colorama 0.3.9 py37_0
comtypes 1.1.7 py37_0
conda 4.5.11 py37_0
conda-build 3.15.1 py37_0
conda-env 2.6.0 1
console_shortcut 0.1.1 3
constantly 15.1.0 py37h28b3542_0
contextlib2 0.5.5 py37_0
cryptography 2.3.1 py37h74b6da3_0
curl 7.61.1 h7602738_0
cycler 0.10.0 py37_0
cython 0.28.5 py37h6538335_0
cytoolz 0.9.0.1 py37hfa6e2cd_1
dask 0.19.2 py37_0
dask-core 0.19.2 py37_0
datashape 0.5.4 py37_1
decorator 4.3.0 py37_0
defusedxml 0.5.0 py37_1
distributed 1.23.2 py37_0
docutils 0.14 py37_0
entrypoints 0.2.3 py37_2
et_xmlfile 1.0.1 py37_0
fastcache 1.0.2 py37hfa6e2cd_2
filelock 3.0.8 py37_0
flask 1.0.2 py37_1
flask-cors 3.0.6 py37_0
freetype 2.9.1 ha9979f8_1
get_terminal_size 1.0.0 h38e98db_0
gevent 1.3.6 py37hfa6e2cd_0
glob2 0.6 py37_1
greenlet 0.4.15 py37hfa6e2cd_0
h5py 2.8.0 py37h3bdd7fb_2
hdf5 1.10.2 hac2f561_1
heapdict 1.0.0 py37_2
html5lib 1.0.1 py37_0
hyperlink 18.0.0 py37_0
icc_rt 2017.0.4 h97af966_0
icu 58.2 ha66f8fd_1
idna 2.7 py37_0
imageio 2.4.1 py37_0
imagesize 1.1.0 py37_0
incremental 17.5.0 py37_0
intel-openmp 2019.0 118
ipykernel 4.10.0 py37_0
ipython 6.5.0 py37_0
ipython_genutils 0.2.0 py37_0
ipywidgets 7.4.2 py37_0
isort 4.3.4 py37_0
itsdangerous 0.24 py37_1
jdcal 1.4 py37_0
jedi 0.12.1 py37_0
jinja2 2.10 py37_0
jpeg 9b hb83a4c4_2
jsonschema 2.6.0 py37_0
jupyter 1.0.0 py37_7
jupyter-contrib-core 0.3.3 <pip>
jupyter-nbextensions-configurator 0.4.0 <pip>
jupyter_client 5.2.3 py37_0
jupyter_console 5.2.0 py37_1
jupyter_core 4.4.0 py37_0
jupyterlab 0.34.9 py37_0
jupyterlab_launcher 0.13.1 py37_0
keyring 13.2.1 py37_0
kiwisolver 1.0.1 py37h6538335_0
lazy-object-proxy 1.3.1 py37hfa6e2cd_2
libcurl 7.61.1 h7602738_0
libiconv 1.15 h1df5818_7
libpng 1.6.34 h79bbb47_0
libsodium 1.0.16 h9d3ae62_0
libssh2 1.8.0 hd619d38_4
libtiff 4.0.9 h36446d0_2
libxml2 2.9.8 hadb2253_1
libxslt 1.1.32 hf6f1972_0
llvmlite 0.24.0 py37h6538335_0
locket 0.2.0 py37_1
lxml 4.2.5 py37hef2cd61_0
lzo 2.10 h6df0209_2
m2w64-gcc-libgfortran 5.3.0 6
m2w64-gcc-libs 5.3.0 7
m2w64-gcc-libs-core 5.3.0 7
m2w64-gmp 6.1.0 2
m2w64-libwinpthread-git 5.0.0.4634.697f757 2
markupsafe 1.0 py37hfa6e2cd_1
matplotlib 3.0.0 py37hd159220_0
mccabe 0.6.1 py37_1
menuinst 1.4.14 py37hfa6e2cd_0
mistune 0.8.3 py37hfa6e2cd_1
mkl 2019.0 118
mkl-service 1.1.2 py37hb217b18_5
mkl_fft 1.0.6 py37hdbbee80_0
mkl_random 1.0.1 py37h77b88f5_1
more-itertools 4.3.0 py37_0
mpmath 1.0.0 py37_2
msgpack-python 0.5.6 py37he980bc4_1
msys2-conda-epoch 20160418 1
multipledispatch 0.6.0 py37_0
navigator-updater 0.2.1 py37_0
nbconvert 5.3.1 py37_0
nbformat 4.4.0 py37_0
networkx 2.1 py37_0
nltk 3.3.0 py37_0
nose 1.3.7 py37_2
notebook 5.6.0 py37_0
numba 0.39.0 py37h830ac7b_0
numexpr 2.6.8 py37h9ef55f4_0
numpy 1.15.2 py37ha559c80_0
numpy 1.15.2 <pip>
numpy-base 1.15.2 py37h8128ebf_0
numpydoc 0.8.0 py37_0
odo 0.5.1 py37_0
olefile 0.46 py37_0
openpyxl 2.5.8 py37_0
openssl 1.0.2p hfa6e2cd_0
packaging 17.1 py37_0
pandas 0.23.4 py37h830ac7b_0
pandoc 2.2.3.2 0
pandocfilters 1.4.2 py37_1
parso 0.3.1 py37_0
partd 0.3.8 py37_0
path.py 11.1.0 py37_0
pathlib2 2.3.2 py37_0
patsy 0.5.0 py37_0
pep8 1.7.1 py37_0
pickleshare 0.7.4 py37_0
pillow 5.3.0 py37hdc69c19_0
pip 18.0 <pip>
pip 10.0.1 py37_0
pkginfo 1.4.2 py37_1
pluggy 0.7.1 py37h28b3542_0
ply 3.11 py37_0
prometheus_client 0.3.1 py37h28b3542_0
prompt_toolkit 1.0.15 py37_0
psutil 5.4.7 py37hfa6e2cd_0
py 1.6.0 py37_0
pyasn1 0.4.4 py37h28b3542_0
pyasn1-modules 0.2.2 py37_0
pycodestyle 2.4.0 py37_0
pycosat 0.6.3 py37hfa6e2cd_0
pycparser 2.19 py37_0
pycrypto 2.6.1 py37hfa6e2cd_9
pycurl 7.43.0.2 py37h74b6da3_0
pyflakes 2.0.0 py37_0
pygments 2.2.0 py37_0
pylint 2.1.1 py37_0
pyodbc 4.0.24 py37h6538335_0
pyopenssl 18.0.0 py37_0
pyparsing 2.2.1 py37_0
pyqt 5.9.2 py37h6538335_2
pysocks 1.6.8 py37_0
pytables 3.4.4 py37he6f6034_0
pytest 3.8.1 py37_0
pytest-arraydiff 0.2 py37h39e3cac_0
pytest-astropy 0.4.0 py37_0
pytest-doctestplus 0.1.3 py37_0
pytest-openfiles 0.3.0 py37_0
pytest-remotedata 0.3.0 py37_0
python 3.7.0 hea74fb7_0
python-dateutil 2.7.3 py37_0
pytz 2018.5 py37_0
pywavelets 1.0.0 py37h452e1ab_0
pywin32 223 py37hfa6e2cd_1
pywinpty 0.5.4 py37_0
pyyaml 3.13 py37hfa6e2cd_0
pyzmq 17.1.2 py37hfa6e2cd_0
pyzmq 17.1.2 <pip>
qt 5.9.6 vc14h1e9a669_2 [vc14]
qtawesome 0.5.0 py37_0
qtconsole 4.4.1 py37_0
qtpy 1.5.1 py37_0
requests 2.19.1 py37_0
rope 0.11.0 py37_0
ruamel_yaml 0.15.46 py37hfa6e2cd_0
scikit-image 0.14.0 py37h6538335_1
scikit-learn 0.20.0 py37heebcf9a_1
scipy 1.1.0 py37h4f6bf74_1
seaborn 0.9.0 py37_0
selenium 3.14.1 <pip>
send2trash 1.5.0 py37_0
service_identity 17.0.0 py37h28b3542_0
setuptools 40.2.0 py37_0
simplegeneric 0.8.1 py37_2
singledispatch 3.4.0.3 py37_0
sip 4.19.8 py37h6538335_0
six 1.11.0 py37_1
snappy 1.1.7 h777316e_3
snowballstemmer 1.2.1 py37_0
sortedcollections 1.0.1 py37_0
sortedcontainers 2.0.5 py37_0
sphinx 1.8.1 py37_0
sphinxcontrib 1.0 py37_1
sphinxcontrib-websupport 1.1.0 py37_1
spyder 3.3.1 py37_1
spyder-kernels 0.2.6 py37_0
sqlalchemy 1.2.12 py37he774522_0
sqlite 3.25.2 hfa6e2cd_0
statsmodels 0.9.0 py37h452e1ab_0
sympy 1.3 py37_0
tblib 1.3.2 py37_0
terminado 0.8.1 py37_1
testpath 0.3.1 py37_0
tk 8.6.8 hfa6e2cd_0
toolz 0.9.0 py37_0
tornado 5.1.1 py37hfa6e2cd_0
tqdm 4.26.0 py37h28b3542_0
traitlets 4.3.2 py37_0
twisted 18.7.0 py37hfa6e2cd_1
typing 3.6.6 <pip>
unicodecsv 0.14.1 py37_0
urllib3 1.23 py37_0
vc 14.1 h0510ff6_4
vega-datasets 0.5.0 <pip>
vs2015_runtime 14.15.26706 h3a45250_0
wcwidth 0.1.7 py37_0
webencodings 0.5.1 py37_1
werkzeug 0.14.1 py37_0
wheel 0.31.1 py37_0
widgetsnbextension 3.4.2 py37_0
win_inet_pton 1.0.1 py37_1
win_unicode_console 0.5 py37_0
wincertstore 0.2 py37_0
winpty 0.4.3 4
wrapt 1.10.11 py37hfa6e2cd_2
xlrd 1.1.0 py37_1
xlsxwriter 1.1.1 py37_0
xlwings 0.11.8 py37_0
xlwt 1.3.0 py37_0
yaml 0.1.7 hc54c509_2
zeromq 4.2.5 he025d50_1
zict 0.1.3 py37_0
zlib 1.2.11 h8395fce_2
zmq 0.0.0 <pip>
zope 1.0 py37_1
zope.interface 4.5.0 py37hfa6e2cd_0
Thanks!
Issue Analytics
- State:
- Created 5 years ago
- Comments:7 (3 by maintainers)
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Could you try adding
alt.data_transformers.enable('json')to your notebook?More information here that may be helpful
Oh, now that I look more closely… when you say
float64(3), are you saying that your data types are structured, with three values in one?