...I created some Cosmic Microwave Background data to plot as a Mollweide projection.

I need some help to find what is the package, the syntax to make a Mollweide plot.

```
> df0
# A tibble: 3,072 x 8
index ind x y z theta phi density
<dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 6144 0.23 0.00830 0.00830 0.230 0.0510 0.785 -0.124
2 6145 0.23 -0.00830 0.00830 0.230 0.0510 2.36 0.0613
3 6146 0.23 -0.00830 -0.00830 0.230 0.0510 3.93 -0.407
4 6147 0.23 0.00830 -0.00830 0.230 0.0510 5.50 -0.527
5 6148 0.23 0.0217 0.00897 0.229 0.102 0.393 -1.32
6 6149 0.23 0.00897 0.0217 0.229 0.102 1.18 -1.49
7 6150 0.23 -0.00897 0.0217 0.229 0.102 1.96 -0.0184
8 6151 0.23 -0.0217 0.00897 0.229 0.102 2.75 0.761
9 6152 0.23 -0.0217 -0.00897 0.229 0.102 3.53 0.205
10 6153 0.23 -0.00897 -0.0217 0.229 0.102 4.32 -0.357
```

I am returning to R just to create this shinyapp. I need to plot (theta, phi) with the color controlled by density.

This is the current state of the shinyapp

https://qsnyc.shinyapps.io/UniverseMap/?_ga=2.263388808.509163910.1601941058-1505942256.1600516222

I don't see it as useful, so I need to create the Mollweide plot.

Any help would be welcomed.

Thanks

PS - This is the python code to generate the data if needed

```
import healpy as hp
import numpy as np
import pandas as pd
from matplotlib import cm
from scipy.stats import norm
nside=16
xx, yy, zz = hp.pix2vec(nside=nside, ipix=np.arange(hp.nside2npix(nside)))
ones = np.ones(xx.shape[0])
theta, phi = hp.pix2ang(nside=nside, ipix=np.arange(hp.nside2npix(nside)))
df = pd.DataFrame(np.empty([0,7]), columns=["ind","x","y","z","theta","phi","density"])
df1 = pd.DataFrame(np.empty([0,7]), columns=["ind","x","y","z","theta","phi","density"])
for r in np.linspace(0.01, 1.0, 10):
df.ind=r*ones
df.x=xx*r
df.y=yy*r
df.z=zz*r
df.theta=theta
df.phi=phi
df.density=np.random.rand(xx.shape[0])
title="Radius={}".format(r)
mu, sigma = norm.fit(df.density)
df.density =(df.density-mu)/sigma
hp.mollview(df.density.squeeze(), title=title, min=-4 * sigma,
max=4 * sigma, unit="K", cmap=cm.RdBu_r)
df1 = pd.concat([df1,df])
df1=df1.reset_index()
df1["index"]=df1.index
df1.to_feather("df.feather")
```

and here the selection by "ind" in the R script:

```
library(feather)
library(mapproj)
library(ggpubr)
df <- feather::read_feather('./df.feather')
# https://cran.r-project.org/web/packages/ebirdst/vignettes/ebirdst-intro-mapping.html
ind <- unique(df$ind)
df0 <- df[df$ind==ind[3],]
x <- df0$theta*180/pi
y <- df0$phi*180/pi
mapproject(x, y,"mollweide")
ggscatter(df0, x="x",y="y",color="density", pallete="jco", main="Univerrse Map")
```

I am trying to use ggscatter but can't figure out how to choose the projection