Mailman 3 March 2020 - Matplotlib-users

Connect plot in Contourf when there are missing values(nan)
by apu April 4, 2020

April 4, 2020

I am plotting x, y, z values using contourf plots. However I have some missing z values (nan). All these regions are shown as blanks and the graph looks diconnected. Is there a way for the plot to have connected gaps? Plotly has an option to connect gaps with smooth transitions? https://plot.ly/python/contour-plots/#connect-the-gaps-between-none-values-… Do we have an equivalent of this in matlotlib contourf plots? -- Sent from: http://matplotlib.1069221.n5.nabble.com/matplotlib-users-f3.html

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Re: [Matplotlib-users] Fwd: Fwd: matplotlib - extend x-axis labels and scaling problem
by Duncan Kerr March 26, 2020

March 26, 2020

> > I have a couple of issues, trying to plot two y axes. How do I > > make grid cover whole area of plot > > make xaxis labels go all way to right > > make both y axes use same scale > > get a legend for both plots onto the graph. > > my graph and code are as follows: > > #!c:/python/python import sys > import numpyas np > import pandasas pd > import matplotlibas mpl > import matplotlib.pyplotas plt > import seabornas sns > import warnings; > > warnings.filterwarnings(action='once') > > plt.style.use('seaborn-whitegrid') > sns.set_style("white") > > cl1='red' cl2='blue' cl3='grey' print("expected title filter1 filter3 file1 file2") > print("called with "+sys.argv[1]+","+sys.argv[2]+","+sys.argv[3]+","+sys.argv[4]) > # Version print(mpl.__version__)# > 3.0.0 print(sns.__version__)# > 0.9.0 # Import Data dfr = pd.read_csv(sys.argv[4]) > dfs = pd.read_csv(sys.argv[5]) > xyr = dfr.groupby(['c1']).count()['c2'] > xys = dfs.groupby(['c1']).count()['c2'] > > fig, ax = plt.subplots(1,1,figsize=(16,9),dpi=90) > > # print data for plots print(dfr.groupby('c1').count()) > > dfr.groupby(['c1']).count()['c2'].plot(ax=ax,color=cl1,label='leftfilter') > > # Decorations # ax1 (left Y axis) ax.set_xlabel('time',color=cl3,fontsize=20) > ax.tick_params(axis='x',rotation=0,labelcolor=cl3,labelsize=12) > ax.set_ylabel(sys.argv[2],color=cl1,fontsize=20) > ax.tick_params(axis='y',rotation=0,labelcolor=cl1) > ax.grid(alpha=.4) > s ="%s min %d max %d avg %d std %d" % ( > sys.argv[1], dfr.groupby('c1').count().min()['c2'], dfr.groupby('c1').count().max()['c2'], > dfr.groupby('c1').count().mean()['c2'], dfs.groupby('c1').count().std()['c2']) > ax.set_title(s,color=cl3) > > > # ax2 (right Y axis) ax2 = ax.twinx()# instantiate a second axes that shares the same x-axis ax2.tick_params(axis='x',rotation=0,labelcolor=cl3,labelsize=12) > dfs.groupby(['c1']).count()['c2'].plot(ax=ax2,color=cl2) > ax2.set_ylabel(sys.argv[3],color=cl2,fontsize=20) > ax2.tick_params(axis='y',labelcolor=cl2) > fig.tight_layout() > # place legend in good spot #plt.legend(loc=0) plt.show() >

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Reshaping Tabular Data to Column Data
by Benson, Randall March 25, 2020

March 25, 2020

Hi - I seem to be stuck here trying to convert downloaded data that is in tabular form since I need to analyze it in single column format. The data is from here and I'm using read_csv as shown below - pnadata1= pd.read_csv('https://www.esrl.noaa.gov/psd/data/correlation/pna.data') The downloaded data looks like this with the values in months 1-12 across the columns below for each year 1948-present - 1948 2020 0 1948 -99.90 -99.90 -99.90 -99.90 -99.90 -99.9... 1 1949 -99.90 -99.90 -99.90 -99.90 -99.90 -99.9... 2 1950 -3.65 -1.69 -0.06 -0.23 -0.40 -1.9... 3 1951 -1.18 -2.11 -1.09 0.47 1.19 -0.5... 4 1952 -3.19 0.08 -0.69 0.89 -0.79 0.5... And, I need it to be reshaped to look like this in yyyymm values format so I can compare it easily to other downloaded data in the column format - 194801 -99.90 194802 -99.90 194803 -99.90 ... 202001 -3.45 202002 0.87 I've tried working with "melt" and "group" in different combinations but cannot figure it out given the online references. Thank you, Randall [Description: cid:image001.jpg@01D34737.23261CB0] Randall P. Benson, PhD Wind Asset Meteorologist, Energy Resource - Onshore 1125 NW Couch Street, Suite 700 Portland, Oregon, USA 97209 Telephone 503-796-7129 Cell 971-227-2477 randall.benson(a)avangrid.com<mailto:randall.benson@avangrid.com> [Description: cid:image002.png@01D34737.23261CB0] In the interest of the environment, please print only if necessary and recycle. ============================================================== Please consider the environment before printing this email. If you have received this message in error, please notify the sender and immediately delete this message and any attachment hereto and/or copy hereof, as such message contains confidential information intended solely for the individual or entity to whom it is addressed. The use or disclosure of such information to third parties is prohibited by law and may give rise to civil or criminal liability. The views presented in this message are solely those of the author(s) and do not necessarily represent the opinion of Avangrid Renewables, LLC. or any company of its group. Neither Avangrid Renewables, LLC. nor any company of its group guarantees the integrity, security or proper receipt of this message. Likewise, neither Avangrid Renewables, LLC. nor any company of its group accepts any liability whatsoever for any possible damages arising from, or in connection with, data interception, software viruses or manipulation by third parties. ==============================================================

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Re: [Matplotlib-users] trouble removing tick labels
by Slavin, Jonathan March 23, 2020

March 23, 2020

Hi Eric, I think I've isolated the problem. In my figure I have been including colorbars for each plot. In my simple example, which I include below, label_outer works without the colorbars but not with them. Regarding using sharey, I am using the same y-axis in each row, but they differ between rows. If I use sharey, things get all messed up - the smaller images are shrunken and only take up part of the figure. In the end I was able to turn off the tick labelling by doing things like: for label in ax.get_yticklabels(which='both'): label.set_visible(False) I think this may have to do with the attributes of axs getting overwritten or something. If I print axs[1,1].get_subplotspec().colspan.start in the case with colorbars I get 0, whereas if I do it without colorbars, I get 1 as I should. Same applies to other axes and to rows. Here's the minimal example: import numpy as np import matplotlib.pyplot as plt fig,axs = plt.subplots(2,2) img0 = np.random.random((10,10)) img1 = np.random.random((10,10)) img2 = np.random.random((10,10)) img3 = np.random.random((10,10)) cax0 = axs[0,0].imshow(img0,extent=[0.,10.,0.,10.]) fig.colorbar(cax0,ax=axs[0,0],pad=0.01) cax1 = axs[0,1].imshow(img1,extent=[0.,10.,0.,10.]) fig.colorbar(cax1,ax=axs[0,1],pad=0.01) cax2 = axs[1,0].imshow(img2,extent=[0.,10.,0.,10.]) fig.colorbar(cax2,ax=axs[1,0],pad=0.01) cax3 = axs[1,1].imshow(img3,extent=[0.,10.,0.,10.]) fig.colorbar(cax3,ax=axs[1,1],pad=0.01) for ax in axs.flat: ax.label_outer() plt.show() On Fri, Mar 20, 2020 at 11:04 AM <matplotlib-users-request(a)python.org> wrote: > Date: Thu, 19 Mar 2020 12:42:31 -1000 > From: Eric Firing <efiring(a)hawaii.edu> > To: matplotlib-users(a)python.org > Subject: Re: [Matplotlib-users] trouble removing tick labels > Message-ID: <77e44a65-c519-705e-24ad-dc13f7c204c3(a)hawaii.edu> > Content-Type: text/plain; charset=utf-8; format=flowed > > Jon, > > If you are removing the tick labels it suggests that the y-axes are all > matched, in which case using > > fig, axs = plt.subplots(2, 2, sharey=True) > > should do what you want. > > If not, please supply a minimal but complete example illustrating the > problem. > > Eric > > On 2020/03/19 11:36 AM, Slavin, Jonathan wrote: > > Hi, > > > > I'm making a plot that's a grid of 4 x 4 axes. I'd like to remove the > > tick labels for the y axes that are not in the first column. I tried > > using what I saw in an example: > > for ax in axs.flat: > > ? ? ax.label_outer() > > but that seems to have no effect. I found where the code that defines > > that function is and tried to use that code directly: > > for ax in axs.flat: > > ? ? if ax.colNum != 0: > > ? ? ? ? for label in ax.get_yticklabels(which='both'): > > ? ? ? ? ? ? label.set_visible(False) > > ? ? ? ? ax.get_yaxis().get_offset_text().set_visible(False) > > ? ? ? ? ax.set_ylabel("") > > but again no effect. Does anyone have any ideas why these are not > > working? Any help would be appreciated. > > > > Regards, > > Jon > -- Jonathan D. Slavin Astrophysicist - High Energy Astrophysics Division Center for Astrophysics | Harvard & Smithsonian Office: (617) 496-7981 | Cell: (781) 363-0035 60 Garden Street | MS 83 | Cambridge, MA 02138

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GSOC 2020
by Utkarsh Bisaria March 22, 2020

March 22, 2020

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[ANN] Matplotlib 3.2.1 release
by Elliott Sales de Andrade March 21, 2020

March 21, 2020

Hi all, I'm a bit late on this, but Matplotlib 3.2.1 was released a couple days ago. This is the first bugfix release of the 3.2.x series. This release contains several critical bug-fixes: * fix Quiver.set_UVC calls with scalar inputs * fix bezier.get_parallels failure from floating point rounding errors * fix markers specified as tuples (polygons, stars, or asterisks) * fix saving PNGs to file objects in some places * fix saving figures using the nbAgg/notebook backend * fix saving with tight layout using the PGF backend * fix setting custom datapath in rcParams (note: it is still deprecated) * fix various issues running setup.py in non-CI environments * fix xpdf distiller * various minor bug and documentation fixes PS, since there was no release announcement for 3.2.0, here are its release notes: * default image interpolation is now `'antialiased'` to better handle down-sampling and reduce artifacts when up-sampling by small ratios. * change when ticks switch to using an offset to improve readability * improvements to auto-scaling and auto-limits * `DivergingNorm` has been renamed to `TwoSlopeNorm` * support for 3 and 4 digit hex colors (`#123` maps to `#112233`) * improvements to Logit scale ticker and formatter * control of where errorbars start getting placed with `errorevery` * correct kerning when laying out text * improvements to MovieRegistry For the full details please see the whats new [1] and API changes [2] in the documentation [1] https://matplotlib.org/3.2.0/users/whats_new.html [2] https://matplotlib.org/3.2.0/api/api_changes.html PPS, for packagers, only: Since I tagged this release, and not Thomas, it is signed by my GPG key. The fingerprint is: 23CA B59E 3332 F94D 26BE F037 8D86 E7FA E5EB 0C10 and it is also used to sign this message. -- Elliott

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Re: [Matplotlib-users] EXTERNAL: Re: Variability Plots Matplotlib NetCDF4 Data
by Hannah March 20, 2020

March 20, 2020

try stdna.squeeze().plot() ? I tried to make a minimum reproduction & I can't reproduce the error. Any chance you can share a binder or how you're getting your data? This is what I tried: slp = np.random.random(([1, 73,144])) stdn = xr.Dataset({'slp': (['month', 'lat', 'lon'], slp)}) stdna = stdn.to_array()# must convert the xarray "dataset" to "dataArray"!!! print(stdna.shape) stdna = stdna.rename('Standardized SLP Anomaly') ax = plt.axes(projection=ccrs.PlateCarree()) ax.coastlines(lw=1) stdna.plot() On Thu, Mar 19, 2020 at 5:52 PM Benson, Randall <Randall.Benson(a)avangrid.com> wrote: > Hi - > > I solved it by converting the datasets to dataarrays using this below with > my variable a dataArray “stdna” and calling the “plot” command. > > However, when I try to plot this variable using -- stdna.plot.contourf() – > but I get an error saying my data must be 2D. The “stnda” variable looks > like this – > > > > stdna > > Out[181]: > > <xarray.DataArray 'Standardized SLP Anomaly' (variable: 1, month: 1, lat: > 73, lon: 144)> > > dask.array<stack, shape=(1, 1, 73, 144), dtype=float32, chunksize=(1, 1, > 73, 144), chunktype=numpy.ndarray> > > Coordinates: > > * lon (lon) float32 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 > 357.5 > > * lat (lat) float32 90.0 87.5 85.0 82.5 80.0 ... -82.5 -85.0 -87.5 > -90.0 > > * month (month) int64 1 > > * variable (variable) <U3 'slp' > > -------------------------------------------------------------- > > This works below…. > > stdna = stdn.to_array()# must convert the xarray "dataset" to > "dataArray"!!! > > #stdna.rename('Standardized SLP Anomaly')#rename dataarray > > stdna = stdna.rename('Standardized SLP Anomaly')#for legend description > label > > # Define an axes object with a projection > > ax = plt.axes(projection=ccrs.PlateCarree()) > > # Plot the coastline > > ax.coastlines(lw=1) > > stdna.plot() > > > > # > > > > *From:* Hannah <story645(a)gmail.com> > *Sent:* Thursday, March 19, 2020 1:32 PM > *To:* Benson, Randall <Randall.Benson(a)avangrid.com> > *Cc:* Matplotlib-users <matplotlib-users(a)python.org> > *Subject:* Re: EXTERNAL: Re: [Matplotlib-users] Variability Plots > Matplotlib NetCDF4 Data > > > > Hi, > > Sorry for the late reply, been swamped. If you haven't sorted this out, > can you please post at least some of the code that generated this error? > > Thanks! > > > > On Tue, Mar 17, 2020 at 1:06 AM Benson, Randall < > Randall.Benson(a)avangrid.com> wrote: > > Hi Hannah – > > > > Are you familiar with this error using xarray to plot gridded netcd4 data? > > > > This is the out from “stdn.var” > > > > <bound method ImplementsDatasetReduce._reduce_method.<locals>.wrapped_func > of <xarray.Dataset> > > Dimensions: (lat: 73, lon: 144, month: 1) > > Coordinates: > > * month (month) int64 2 > > * lon (lon) float32 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5 > > * lat (lat) float32 90.0 87.5 85.0 82.5 80.0 ... -82.5 -85.0 -87.5 > -90.0 > > Data variables: > > slp (month, lat, lon) float32 dask.array<chunksize=(1, 73, 144), > meta=np.ndarray>> > > > > I keep getting this error – > > - AttributeError: '_Dataset_PlotMethods' object has no attribute 'contourf' > > > > Thank you, > > Randall > > > > *From:* Hannah <story645(a)gmail.com> > *Sent:* Wednesday, March 11, 2020 4:28 PM > *To:* Benson, Randall <Randall.Benson(a)avangrid.com> > *Cc:* Matplotlib-users <matplotlib-users(a)python.org> > *Subject:* EXTERNAL: Re: [Matplotlib-users] Variability Plots Matplotlib > NetCDF4 Data > > > > Hi Randall, > > I'm not sure what specifically you're asking for. Are you using xarray ( > http://xarray.pydata.org/en/stable/) ? If not, it might help in more > efficiently computing the anomolies once you read all the files into an > xarray: > > > > > http://xarray.pydata.org/en/stable/examples/weather-data.html#Calculate-mon… > > On Wed, Mar 11, 2020, 4:17 PM Benson, Randall <Randall.Benson(a)avangrid.com> > wrote: > > HI- > > > > I’m trying to develop monthly standardized anomaly plots of Sea Level > Pressure (SLP) using NCEP reanalysis data in netCDF4 format. I can plot > netCDF4 data for a single month in plot form like the example shown below. > However, I need to construct average SLP plots for each month given a set > of years and use those to plot the standardized anomalies for each month of > the current year. So, I’m looking too for just examples (python code) of > creating variability plots using gridded data in Matplotlib. Thank you! > > > > Randall Benson > > > > *Randall P. Benson, PhD* > Wind Asset Meteorologist, Energy Resource - Onshore > > 1125 NW Couch Street, Suite 700 > > Portland, Oregon, USA 97209 > Telephone 503-796-7129 > Cell 971-227-2477 > randall.benson(a)avangrid.com > > > > In the interest of the environment, > please print only if necessary and recycle. > > > > > > > > ============================================================== > > > > Please consider the environment before printing this email. > > > > If you have received this message in error, please notify the sender and immediately delete this message and any attachment hereto and/or copy hereof, as such message contains confidential information intended solely for the individual or entity to whom it is addressed. The use or disclosure of such information to third parties is prohibited by law and may give rise to civil or criminal liability. > > > > The views presented in this message are solely those of the author(s) and do not necessarily represent the opinion of Avangrid Renewables, LLC. or any company of its group. Neither Avangrid Renewables, LLC. nor any company of its group guarantees the integrity, security or proper receipt of this message. Likewise, neither Avangrid Renewables, LLC. nor any company of its group accepts any liability whatsoever for any possible damages arising from, or in connection with, data interception, software viruses or manipulation by third parties. > > > > ============================================================== > > _______________________________________________ > Matplotlib-users mailing list > Matplotlib-users(a)python.org > https://mail.python.org/mailman/listinfo/matplotlib-users > > ============================================================== > > > > Please consider the environment before printing this email. > > > > If you have received this message in error, please notify the sender and immediately delete this message and any attachment hereto and/or copy hereof, as such message contains confidential information intended solely for the individual or entity to whom it is addressed. The use or disclosure of such information to third parties is prohibited by law and may give rise to civil or criminal liability. > > > > The views presented in this message are solely those of the author(s) and do not necessarily represent the opinion of Avangrid Renewables, LLC. or any company of its group. Neither Avangrid Renewables, LLC. nor any company of its group guarantees the integrity, security or proper receipt of this message. Likewise, neither Avangrid Renewables, LLC. nor any company of its group accepts any liability whatsoever for any possible damages arising from, or in connection with, data interception, software viruses or manipulation by third parties. > > > > ============================================================== > > > > ============================================================== > > Please consider the environment before printing this email. > > If you have received this message in error, please notify the sender and immediately delete this message and any attachment hereto and/or copy hereof, as such message contains confidential information intended solely for the individual or entity to whom it is addressed. The use or disclosure of such information to third parties is prohibited by law and may give rise to civil or criminal liability. > > The views presented in this message are solely those of the author(s) and do not necessarily represent the opinion of Avangrid Renewables, LLC. or any company of its group. Neither Avangrid Renewables, LLC. nor any company of its group guarantees the integrity, security or proper receipt of this message. Likewise, neither Avangrid Renewables, LLC. nor any company of its group accepts any liability whatsoever for any possible damages arising from, or in connection with, data interception, software viruses or manipulation by third parties. > > ============================================================== > >

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Transparency for pcolor slices in Axes3D plot
by Thibaut Appel March 20, 2020

March 20, 2020

Dear matplotlib users/developers, I struggle to set some transparency in an Axes3D plot with series of 2D-slices generated with pcolor. In spite of trying to set alpha, all the slices remain opaque. I've just posted the issue on stackoverflow <https://stackoverflow.com/questions/60776103/how-to-enforce-transparency-fo…>, where you can see an illustration of the problem. Would someone have a workaround? |import numpy as np| |import matplotlib.pyplot as plt| |from mpl_toolkits.mplot3d import Axes3D| |from matplotlib.collections import PolyCollection| || |X, Y = np.meshgrid(x,y)| || |fig = plt.figure()| |ax = fig.gca(projection='3d')| || |alpha = 0.8| || |for i in range(len(islices)):| | im = ax.pcolor(X,Y,u[islices[i],:,:]) #,alpha=alpha)| | #im.set_facecolor((0, 0, 1, alpha))| |||ax.add_collection3d(im,zs=xslices[i],zdir='y')|| | |plt.show()| Thank you in advance. ||

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trouble removing tick labels
by Slavin, Jonathan March 19, 2020

March 19, 2020

Hi, I'm making a plot that's a grid of 4 x 4 axes. I'd like to remove the tick labels for the y axes that are not in the first column. I tried using what I saw in an example: for ax in axs.flat: ax.label_outer() but that seems to have no effect. I found where the code that defines that function is and tried to use that code directly: for ax in axs.flat: if ax.colNum != 0: for label in ax.get_yticklabels(which='both'): label.set_visible(False) ax.get_yaxis().get_offset_text().set_visible(False) ax.set_ylabel("") but again no effect. Does anyone have any ideas why these are not working? Any help would be appreciated. Regards, Jon -- Jonathan D. Slavin Astrophysicist - High Energy Astrophysics Division Center for Astrophysics | Harvard & Smithsonian Office: (617) 496-7981 | Cell: (781) 363-0035 60 Garden Street | MS 83 | Cambridge, MA 02138

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Re: [Matplotlib-users] EXTERNAL: Re: Variability Plots Matplotlib NetCDF4 Data
by Hannah March 19, 2020

March 19, 2020

Hi, Sorry for the late reply, been swamped. If you haven't sorted this out, can you please post at least some of the code that generated this error? Thanks! On Tue, Mar 17, 2020 at 1:06 AM Benson, Randall <Randall.Benson(a)avangrid.com> wrote: > Hi Hannah – > > > > Are you familiar with this error using xarray to plot gridded netcd4 data? > > > > This is the out from “stdn.var” > > > > <bound method ImplementsDatasetReduce._reduce_method.<locals>.wrapped_func > of <xarray.Dataset> > > Dimensions: (lat: 73, lon: 144, month: 1) > > Coordinates: > > * month (month) int64 2 > > * lon (lon) float32 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5 > > * lat (lat) float32 90.0 87.5 85.0 82.5 80.0 ... -82.5 -85.0 -87.5 > -90.0 > > Data variables: > > slp (month, lat, lon) float32 dask.array<chunksize=(1, 73, 144), > meta=np.ndarray>> > > > > I keep getting this error – > > - AttributeError: '_Dataset_PlotMethods' object has no attribute 'contourf' > > > > Thank you, > > Randall > > > > *From:* Hannah <story645(a)gmail.com> > *Sent:* Wednesday, March 11, 2020 4:28 PM > *To:* Benson, Randall <Randall.Benson(a)avangrid.com> > *Cc:* Matplotlib-users <matplotlib-users(a)python.org> > *Subject:* EXTERNAL: Re: [Matplotlib-users] Variability Plots Matplotlib > NetCDF4 Data > > > > Hi Randall, > > I'm not sure what specifically you're asking for. Are you using xarray ( > http://xarray.pydata.org/en/stable/) ? If not, it might help in more > efficiently computing the anomolies once you read all the files into an > xarray: > > > > > http://xarray.pydata.org/en/stable/examples/weather-data.html#Calculate-mon… > > On Wed, Mar 11, 2020, 4:17 PM Benson, Randall <Randall.Benson(a)avangrid.com> > wrote: > > HI- > > > > I’m trying to develop monthly standardized anomaly plots of Sea Level > Pressure (SLP) using NCEP reanalysis data in netCDF4 format. I can plot > netCDF4 data for a single month in plot form like the example shown below. > However, I need to construct average SLP plots for each month given a set > of years and use those to plot the standardized anomalies for each month of > the current year. So, I’m looking too for just examples (python code) of > creating variability plots using gridded data in Matplotlib. Thank you! > > > > Randall Benson > > > > [image: Description: cid:image001.jpg@01D34737.23261CB0] > > *Randall P. Benson, PhD* > Wind Asset Meteorologist, Energy Resource - Onshore > > 1125 NW Couch Street, Suite 700 > > Portland, Oregon, USA 97209 > Telephone 503-796-7129 > Cell 971-227-2477 > randall.benson(a)avangrid.com > > > [image: Description: cid:image002.png@01D34737.23261CB0] > > > In the interest of the environment, > please print only if necessary and recycle. > > > > > > > > ============================================================== > > > > Please consider the environment before printing this email. > > > > If you have received this message in error, please notify the sender and immediately delete this message and any attachment hereto and/or copy hereof, as such message contains confidential information intended solely for the individual or entity to whom it is addressed. The use or disclosure of such information to third parties is prohibited by law and may give rise to civil or criminal liability. > > > > The views presented in this message are solely those of the author(s) and do not necessarily represent the opinion of Avangrid Renewables, LLC. or any company of its group. Neither Avangrid Renewables, LLC. nor any company of its group guarantees the integrity, security or proper receipt of this message. Likewise, neither Avangrid Renewables, LLC. nor any company of its group accepts any liability whatsoever for any possible damages arising from, or in connection with, data interception, software viruses or manipulation by third parties. > > > > ============================================================== > > _______________________________________________ > Matplotlib-users mailing list > Matplotlib-users(a)python.org > https://mail.python.org/mailman/listinfo/matplotlib-users > > ============================================================== > > Please consider the environment before printing this email. > > If you have received this message in error, please notify the sender and immediately delete this message and any attachment hereto and/or copy hereof, as such message contains confidential information intended solely for the individual or entity to whom it is addressed. The use or disclosure of such information to third parties is prohibited by law and may give rise to civil or criminal liability. > > The views presented in this message are solely those of the author(s) and do not necessarily represent the opinion of Avangrid Renewables, LLC. or any company of its group. Neither Avangrid Renewables, LLC. nor any company of its group guarantees the integrity, security or proper receipt of this message. Likewise, neither Avangrid Renewables, LLC. nor any company of its group accepts any liability whatsoever for any possible damages arising from, or in connection with, data interception, software viruses or manipulation by third parties. > > ============================================================== > >

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