Develop Reference

No module named 'matplotlib' after conda installation

I created a new environment and added it to jupyter like this:
conda create --name tf_plot tensorflow matplotlib
conda install -c anaconda ipykernel
python -m ipykernel install --user --name tf_plot
but when I try to
import matplotlib
I get ModuleNotFoundError: No module named 'matplotlib'
conda list shows
_tflow_select 2.3.0 eigen
absl-py 0.13.0 py38haa95532_0
aiohttp 3.7.4.post0 py38h2bbff1b_2
astor 0.8.1 py38haa95532_0
astunparse 1.6.3 py_0
async-timeout 3.0.1 py38haa95532_0
attrs 21.2.0 pyhd3eb1b0_0
blas 1.0 mkl
blinker 1.4 py38haa95532_0
brotli 1.0.9 ha925a31_2
brotlipy 0.7.0 py38h2bbff1b_1003
ca-certificates 2021.10.26 haa95532_2
cachetools 4.2.2 pyhd3eb1b0_0
certifi 2021.10.8 py38haa95532_0
cffi 1.15.0 py38h2bbff1b_0
chardet 4.0.0 py38haa95532_1003
charset-normalizer 2.0.4 pyhd3eb1b0_0
click 8.0.3 pyhd3eb1b0_0
coverage 5.5 py38h2bbff1b_2
cryptography 3.4.8 py38h71e12ea_0
cycler 0.10.0 py38_0
cython 0.29.24 py38h604cdb4_0
dataclasses 0.8 pyh6d0b6a4_7
fonttools 4.25.0 pyhd3eb1b0_0
freetype 2.10.4 hd328e21_0
gast 0.4.0 pyhd3eb1b0_0
google-auth 1.33.0 pyhd3eb1b0_0
google-auth-oauthlib 0.4.4 pyhd3eb1b0_0
google-pasta 0.2.0 pyhd3eb1b0_0
grpcio 1.36.1 py38hc60d5dd_1
h5py 2.10.0 py38h5e291fa_0
hdf5 1.10.4 h7ebc959_0
icc_rt 2019.0.0 h0cc432a_1
icu 58.2 ha925a31_3
idna 3.2 pyhd3eb1b0_0
importlib-metadata 4.8.1 py38haa95532_0
intel-openmp 2021.4.0 haa95532_3556
jpeg 9d h2bbff1b_0
keras-applications 1.0.8 py_1
keras-preprocessing 1.1.2 pyhd3eb1b0_0
kiwisolver 1.3.1 py38hd77b12b_0
libpng 1.6.37 h2a8f88b_0
libprotobuf 3.17.2 h23ce68f_1
libtiff 4.2.0 hd0e1b90_0
libwebp 1.2.0 h2bbff1b_0
lz4-c 1.9.3 h2bbff1b_1
markdown 3.3.4 py38haa95532_0
matplotlib 3.4.3 py38haa95532_0
matplotlib-base 3.4.3 py38h49ac443_0
mkl 2021.4.0 haa95532_640
mkl-service 2.4.0 py38h2bbff1b_0
mkl_fft 1.3.1 py38h277e83a_0
mkl_random 1.2.2 py38hf11a4ad_0
multidict 5.1.0 py38h2bbff1b_2
munkres 1.1.4 py_0
numpy 1.21.2 py38hfca59bb_0
numpy-base 1.21.2 py38h0829f74_0
oauthlib 3.1.1 pyhd3eb1b0_0
olefile 0.46 pyhd3eb1b0_0
openssl 1.1.1l h2bbff1b_0
opt_einsum 3.3.0 pyhd3eb1b0_1
pillow 8.4.0 py38hd45dc43_0
pip 21.2.2 py38haa95532_0
protobuf 3.17.2 py38hd77b12b_0
pyasn1 0.4.8 pyhd3eb1b0_0
pyasn1-modules 0.2.8 py_0
pycparser 2.21 pyhd3eb1b0_0
pyjwt 2.1.0 py38haa95532_0
pyopenssl 21.0.0 pyhd3eb1b0_1
pyparsing 3.0.4 pyhd3eb1b0_0
pyqt 5.9.2 py38ha925a31_4
pyreadline 2.1 py38_1
pysocks 1.7.1 py38haa95532_0
python 3.8.12 h6244533_0
python-dateutil 2.8.2 pyhd3eb1b0_0
qt 5.9.7 vc14h73c81de_0
requests 2.26.0 pyhd3eb1b0_0
requests-oauthlib 1.3.0 py_0
rsa 4.7.2 pyhd3eb1b0_1
scipy 1.7.1 py38hbe87c03_2
setuptools 58.0.4 py38haa95532_0
sip 4.19.13 py38ha925a31_0
six 1.16.0 pyhd3eb1b0_0
sqlite 3.36.0 h2bbff1b_0
tensorboard 2.4.0 pyhc547734_0
tensorboard-plugin-wit 1.6.0 py_0
tensorflow 2.3.0 mkl_py38h8c0d9a2_0
tensorflow-base 2.3.0 eigen_py38h75a453f_0
tensorflow-estimator 2.6.0 pyh7b7c402_0
termcolor 1.1.0 py38haa95532_1
tk 8.6.11 h2bbff1b_0
tornado 6.1 py38h2bbff1b_0
typing-extensions 3.10.0.2 hd3eb1b0_0
typing_extensions 3.10.0.2 pyh06a4308_0
urllib3 1.26.7 pyhd3eb1b0_0
vc 14.2 h21ff451_1
vs2015_runtime 14.27.29016 h5e58377_2
werkzeug 2.0.2 pyhd3eb1b0_0
wheel 0.37.0 pyhd3eb1b0_1
win_inet_pton 1.1.0 py38haa95532_0
wincertstore 0.2 py38haa95532_2
wrapt 1.12.1 py38he774522_1
xz 5.2.5 h62dcd97_0
yarl 1.6.3 py38h2bbff1b_0
zipp 3.6.0 pyhd3eb1b0_0
zlib 1.2.11 h62dcd97_4
zstd 1.4.9 h19a0ad4_0
This sentence is here because stackoverflow requires me to add more details to this question but I'm not sure what more info can I provide. If this question is unclear in any way please inform me about this in the comments and I'll edit it

Going by the SO answer here the virtual environment named tf_plot needs to be activated first before import. i.e,
conda activate -n tf_plot
Please check conda documentation here for more details

Why is python constantly saying 'ModuleNotFoundError' for a library import when it clearly exists through Anaconda? [duplicate]

This question already has answers here:
How to add package to conda environment without pip
(5 answers)
Closed 1 year ago.
I am trying to use matplotlib and pandas in one of my projects, and the error message I get is confusing me. I have done anything I can to resolve it, but it still doesn't work. There might be a problem with my Anaconda (i am using anaconda python) distribution or a problem with the path, but I checked and the path seemed to point to Anaconda
Every time I write this code:
import matplotlib as plt
import pandas as pd
it says there is an error. The error is:
PS C:\Users\mghaf\Documents\GitHub\Modelling-Cell-Growth-in-CFU> & C:/Users/mghaf/Anaconda3/envs/rstudio/python.exe c:/Users/mghaf/Documents/GitHub/Modelling-Cell-Growth-in-CFU/test.py
Traceback (most recent call last):
File "c:/Users/mghaf/Documents/GitHub/Modelling-Cell-Growth-in-CFU/test.py", line 1, in <module>
import matplotlib as plt
ModuleNotFoundError: No module named 'matplotlib'
And for Pandas:
PS C:\Users\mghaf\Documents\GitHub\Modelling-Cell-Growth-in-CFU> & C:/Users/mghaf/Anaconda3/envs/rstudio/python.exe c:/Users/mghaf/Documents/GitHub/Modelling-Cell-Growth-in-CFU/test.py
Traceback (most recent call last):
File "c:/Users/mghaf/Documents/GitHub/Modelling-Cell-Growth-in-CFU/test.py", line 2, in <module>
import pandas as pd
ModuleNotFoundError: No module named 'pandas'
In vscode, I have checked all the libraries that I have, and it seems that I have everything, yet it still says module not found.
# packages in environment at C:\Users\mghaf\Anaconda3:
#
# Name Version Build Channel
_ipyw_jlab_nb_ext_conf 0.1.0 py38_0
alabaster 0.7.12 py_0
anaconda 2020.11 py38_0
anaconda-client 1.7.2 py38_0
anaconda-navigator 2.0.4 py38_0
anaconda-project 0.8.4 py_0
argh 0.26.2 py38_0
argon2-cffi 20.1.0 py38he774522_1
asn1crypto 1.4.0 py_0
astroid 2.4.2 py38_0
astropy 4.0.2 py38he774522_0
async_generator 1.10 py_0
atomicwrites 1.4.0 py_0
attrs 20.3.0 pyhd3eb1b0_0
autopep8 1.5.4 py_0
babel 2.8.1 pyhd3eb1b0_0
backcall 0.2.0 py_0
backports 1.0 py_2
backports.functools_lru_cache 1.6.1 py_0
backports.shutil_get_terminal_size 1.0.0 py38_2
backports.tempfile 1.0 py_1
backports.weakref 1.0.post1 py_1
bcrypt 3.2.0 py38he774522_0
beautifulsoup4 4.9.3 pyhb0f4dca_0
bitarray 1.6.1 py38h2bbff1b_0
bkcharts 0.2 py38_0
blas 1.0 mkl
bleach 3.2.1 py_0
blosc 1.20.1 h7bd577a_0
bokeh 2.2.3 py38_0
boto 2.49.0 py38_0
bottleneck 1.3.2 py38h2a96729_1
brotlipy 0.7.0 py38he774522_1000
bzip2 1.0.8 he774522_0
ca-certificates 2020.10.14 0
certifi 2020.6.20 pyhd3eb1b0_3
cffi 1.14.3 py38h7a1dbc1_0
chardet 3.0.4 py38_1003
click 7.1.2 py_0
cloudpickle 1.6.0 py_0
clyent 1.2.2 py38_1
colorama 0.4.4 py_0
comtypes 1.1.7 py38_1001
conda 4.10.3 py38haa95532_0
conda-build 3.20.5 py38_1
conda-content-trust 0.1.1 pyhd3eb1b0_0
conda-env 2.6.0 1
conda-package-handling 1.7.2 py38h76e460a_0
conda-repo-cli 1.0.4 pyhd3eb1b0_0
conda-token 0.3.0 pyhd3eb1b0_0
conda-verify 3.4.2 py_1
console_shortcut 0.1.1 4
contextlib2 0.6.0.post1 py_0
cryptography 3.1.1 py38h7a1dbc1_0
curl 7.71.1 h2a8f88b_1
cycler 0.10.0 py38_0
cython 0.29.21 py38ha925a31_0
cytoolz 0.11.0 py38he774522_0
dask 2.30.0 py_0
dask-core 2.30.0 py_0
decorator 4.4.2 py_0
defusedxml 0.6.0 py_0
diff-match-patch 20200713 py_0
distributed 2.30.1 py38haa95532_0
docutils 0.16 py38_1
entrypoints 0.3 py38_0
et_xmlfile 1.0.1 py_1001
fastcache 1.1.0 py38he774522_0
filelock 3.0.12 py_0
flake8 3.8.4 py_0
flask 1.1.2 py_0
freetype 2.10.4 hd328e21_0
fsspec 0.8.3 py_0
future 0.18.2 py38_1
get_terminal_size 1.0.0 h38e98db_0
gevent 20.9.0 py38he774522_0
glob2 0.7 py_0
greenlet 0.4.17 py38he774522_0
h5py 2.10.0 py38h5e291fa_0
hdf5 1.10.4 h7ebc959_0
heapdict 1.0.1 py_0
html5lib 1.1 py_0
icc_rt 2019.0.0 h0cc432a_1
icu 58.2 ha925a31_3
idna 2.10 py_0
imageio 2.9.0 py_0
imagesize 1.2.0 py_0
importlib-metadata 2.0.0 py_1
importlib_metadata 2.0.0 1
iniconfig 1.1.1 py_0
intel-openmp 2020.2 254
intervaltree 3.1.0 py_0
ipykernel 5.3.4 py38h5ca1d4c_0
ipython 7.19.0 py38hd4e2768_0
ipython_genutils 0.2.0 py38_0
ipywidgets 7.5.1 py_1
isort 5.6.4 py_0
itsdangerous 1.1.0 py_0
jdcal 1.4.1 py_0
jedi 0.17.1 py38_0
jinja2 2.11.2 py_0
joblib 0.17.0 py_0
jpeg 9b hb83a4c4_2
json5 0.9.5 py_0
jsonschema 3.2.0 py_2
jupyter 1.0.0 py38_7
jupyter_client 6.1.7 py_0
jupyter_console 6.2.0 py_0
jupyter_core 4.6.3 py38_0
jupyterlab 2.2.6 py_0
jupyterlab_pygments 0.1.2 py_0
jupyterlab_server 1.2.0 py_0
keyring 21.4.0 py38_1
kiwisolver 1.3.0 py38hd77b12b_0
krb5 1.18.2 hc04afaa_0
lazy-object-proxy 1.4.3 py38he774522_0
libarchive 3.4.2 h5e25573_0
libcurl 7.71.1 h2a8f88b_1
libiconv 1.15 h1df5818_7
liblief 0.10.1 ha925a31_0
libpng 1.6.37 h2a8f88b_0
libsodium 1.0.18 h62dcd97_0
libspatialindex 1.9.3 h33f27b4_0
libssh2 1.9.0 h7a1dbc1_1
libtiff 4.1.0 h56a325e_1
libxml2 2.9.10 hb89e7f3_3
libxslt 1.1.34 he774522_0
llvmlite 0.34.0 py38h1a82afc_4
locket 0.2.0 py38_1
lxml 4.6.1 py38h1350720_0
lz4-c 1.9.2 hf4a77e7_3
lzo 2.10 he774522_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 1.1.1 py38he774522_0
matplotlib 3.3.2 0
matplotlib-base 3.3.2 py38hba9282a_0
mccabe 0.6.1 py38_1
menuinst 1.4.16 py38he774522_1
mistune 0.8.4 py38he774522_1000
mkl 2020.2 256
mkl-service 2.3.0 py38hb782905_0
mkl_fft 1.2.0 py38h45dec08_0
mkl_random 1.1.1 py38h47e9c7a_0
mock 4.0.2 py_0
more-itertools 8.6.0 pyhd3eb1b0_0
mpmath 1.1.0 py38_0
msgpack-python 1.0.0 py38h74a9793_1
msys2-conda-epoch 20160418 1
multipledispatch 0.6.0 py38_0
navigator-updater 0.2.1 py38_0
nbclient 0.5.1 py_0
nbconvert 6.0.7 py38_0
nbformat 5.0.8 py_0
nest-asyncio 1.4.2 pyhd3eb1b0_0
networkx 2.5 py_0
nltk 3.5 py_0
nose 1.3.7 py38_2
notebook 6.1.4 py38_0
numba 0.51.2 py38hf9181ef_1
numexpr 2.7.1 py38h25d0782_0
numpy 1.19.2 py38hadc3359_0
numpy-base 1.19.2 py38ha3acd2a_0
numpydoc 1.1.0 pyhd3eb1b0_1
olefile 0.46 py_0
openpyxl 3.0.5 py_0
openssl 1.1.1h he774522_0
packaging 20.4 py_0
pandas 1.1.3 py38ha925a31_0
pandoc 2.11 h9490d1a_0
pandocfilters 1.4.3 py38haa95532_1
paramiko 2.7.2 py_0
parso 0.7.0 py_0
partd 1.1.0 py_0
path 15.0.0 py38_0
path.py 12.5.0 0
pathlib2 2.3.5 py38_0
pathtools 0.1.2 py_1
patsy 0.5.1 py38_0
pep8 1.7.1 py38_0
pexpect 4.8.0 py38_0
pickleshare 0.7.5 py38_1000
pillow 8.0.1 py38h4fa10fc_0
pip 20.2.4 py38haa95532_0
pkginfo 1.6.1 py38haa95532_0
pluggy 0.13.1 py38_0
ply 3.11 py38_0
powershell_shortcut 0.0.1 3
prometheus_client 0.8.0 py_0
prompt-toolkit 3.0.8 py_0
prompt_toolkit 3.0.8 0
psutil 5.7.2 py38he774522_0
py 1.9.0 py_0
py-lief 0.10.1 py38ha925a31_0
pycodestyle 2.6.0 py_0
pycosat 0.6.3 py38he774522_0
pycparser 2.20 py_2
pycurl 7.43.0.6 py38h7a1dbc1_0
pydocstyle 5.1.1 py_0
pyflakes 2.2.0 py_0
pygments 2.7.2 pyhd3eb1b0_0
pylint 2.6.0 py38_0
pynacl 1.4.0 py38h62dcd97_1
pyodbc 4.0.30 py38ha925a31_0
pyopenssl 19.1.0 py_1
pyparsing 2.4.7 py_0
pyqt 5.9.2 py38ha925a31_4
pyreadline 2.1 py38_1
pyrsistent 0.17.3 py38he774522_0
pysocks 1.7.1 py38_0
pytables 3.6.1 py38ha5be198_0
pytest 6.1.1 py38_0
python 3.8.5 h5fd99cc_1
python-dateutil 2.8.1 py_0
python-jsonrpc-server 0.4.0 py_0
python-language-server 0.35.1 py_0
python-libarchive-c 2.9 py_0
pytz 2020.1 py_0
pywavelets 1.1.1 py38he774522_2
pywin32 227 py38he774522_1
pywin32-ctypes 0.2.0 py38_1000
pywinpty 0.5.7 py38_0
pyyaml 5.3.1 py38he774522_1
pyzmq 19.0.2 py38ha925a31_1
qdarkstyle 2.8.1 py_0
qt 5.9.7 vc14h73c81de_0
qtawesome 1.0.1 py_0
qtconsole 4.7.7 py_0
qtpy 1.9.0 py_0
regex 2020.10.15 py38he774522_0
requests 2.24.0 py_0
rope 0.18.0 py_0
rtree 0.9.4 py38h21ff451_1
ruamel_yaml 0.15.87 py38he774522_1
scikit-image 0.17.2 py38h1e1f486_0
scikit-learn 0.23.2 py38h47e9c7a_0
scipy 1.5.2 py38h14eb087_0
seaborn 0.11.0 py_0
send2trash 1.5.0 py38_0
setuptools 50.3.1 py38haa95532_1
simplegeneric 0.8.1 py38_2
singledispatch 3.4.0.3 py_1001
sip 4.19.13 py38ha925a31_0
six 1.15.0 py38haa95532_0
snowballstemmer 2.0.0 py_0
sortedcollections 1.2.1 py_0
sortedcontainers 2.2.2 py_0
soupsieve 2.0.1 py_0
sphinx 3.2.1 py_0
sphinxcontrib 1.0 py38_1
sphinxcontrib-applehelp 1.0.2 py_0
sphinxcontrib-devhelp 1.0.2 py_0
sphinxcontrib-htmlhelp 1.0.3 py_0
sphinxcontrib-jsmath 1.0.1 py_0
sphinxcontrib-qthelp 1.0.3 py_0
sphinxcontrib-serializinghtml 1.1.4 py_0
sphinxcontrib-websupport 1.2.4 py_0
spyder 4.1.5 py38_0
spyder-kernels 1.9.4 py38_0
sqlalchemy 1.3.20 py38h2bbff1b_0
sqlite 3.33.0 h2a8f88b_0
statsmodels 0.12.0 py38he774522_0
sympy 1.6.2 py38haa95532_1
tblib 1.7.0 py_0
terminado 0.9.1 py38_0
testpath 0.4.4 py_0
threadpoolctl 2.1.0 pyh5ca1d4c_0
tifffile 2020.10.1 py38h8c2d366_2
tk 8.6.10 he774522_0
toml 0.10.1 py_0
toolz 0.11.1 py_0
tornado 6.0.4 py38he774522_1
tqdm 4.50.2 py_0
traitlets 5.0.5 py_0
typing_extensions 3.7.4.3 py_0
ujson 4.0.1 py38ha925a31_0
unicodecsv 0.14.1 py38_0
urllib3 1.25.11 py_0
vc 14.1 h0510ff6_4
vs2015_runtime 14.16.27012 hf0eaf9b_3
watchdog 0.10.3 py38_0
wcwidth 0.2.5 py_0
webencodings 0.5.1 py38_1
werkzeug 1.0.1 py_0
wheel 0.35.1 py_0
widgetsnbextension 3.5.1 py38_0
win_inet_pton 1.1.0 py38_0
win_unicode_console 0.5 py38_0
wincertstore 0.2 py38_0
winpty 0.4.3 4
wrapt 1.11.2 py38he774522_0
xlrd 1.2.0 py_0
xlsxwriter 1.3.7 py_0
xlwings 0.20.8 py38_0
xlwt 1.3.0 py38_0
xmltodict 0.12.0 py_0
xz 5.2.5 h62dcd97_0
yaml 0.2.5 he774522_0
yapf 0.30.0 py_0
zeromq 4.3.2 ha925a31_3
zict 2.0.0 py_0
zipp 3.4.0 pyhd3eb1b0_0
zlib 1.2.11 h62dcd97_4
zope 1.0 py38_1
zope.event 4.5.0 py38_0
zope.interface 5.1.2 py38he774522_0
zstd 1.4.5 h04227a9_0
As you can see, matplotlib and pandas are there.
I a using anaconda to get my libraries. I am using Vscode for writing the program.
Maybe I need to do a complete uninstall of python and any attributes to it, and then install anything I need back to get a fresh system?

I can see that the packages already exist in your base environment so there is no need to install any additional packages for now.
First you need to add anaconda to your path.
Please head here and scroll down to add anaconda to path (optional) https://www.datacamp.com/community/tutorials/installing-anaconda-windows and follow the instructions.
Once that it done, You need to type conda activate base in your command prompt and hit enter, then you can type code and you can launch your development environment.
Alternatively, you can look for anaconda prompt within the start button and launch it, it will automatically go into the anaconda base environment, then you can try to launch code by typing code.
If you can’t launch code, you can head here and follow the instructions to add vs code to your path, How to start Visual Studio Code within Anaconda Env just follow the steps in the first answer.
Then open a new CMD prompt and try typing the activate and code commands from above again or launching the anaconda prompt from within the start button again.
Alternatively, you can also add the anaconda environment directly into vs code using the following steps.
1 Ctrl + shift + P
2 Search Select Interpreter
3 Select it and it will show you the list of your virtual environment created via conda and other python versions
4 select the environment and you are ready to go.
Then you will be able to launch into your anaconda environment either by using the command prompt, activating the environment and launching code. Or you can launch code directly and select the anaconda environment from within.
You need to understand what anaconda is, it is just an environment creator and package manager. Each environment has its own packages you can control and destroy when you are done, it ensures that your environments are sandboxed so that they don’t affect one another or your system.
I recommend that you create a new environment, not use the base environment to do your work, to do this you can type conda create -n name where name is the name of the environment you can put whatever you want. After that you can do conda install pandas matplotlib etc and instead of launching into base you can now conda activate name and launch into this environment instead.

From your comment, the environment where the packages are installed in, and the interpreter you want to use are different.
Please do the following from an Anaconda command prompt.
conda activate rstudio
pip install matplotlib
pip install pandas

Error while installed tensor flow on windows

I created my own virtual environment for my work in python anaconda. I installed tensor flow and checked my version as tensorboard 2.3.1 pypi_0 pypi. However, when I am trying to import the following libraries
from keras.models import Sequential
from keras.layers import Dense
from keras.layers import LSTM
But even after installing tensor flow and with an upgraded version, I am getting the following error
`ImportError: Traceback (most recent call last):
File "C:\Users\rp603\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\pywrap_tensorflow.py", line 64, in <module>
from tensorflow.python._pywrap_tensorflow_internal import *
ImportError: DLL load failed: The specified module could not be found.
Failed to load the native TensorFlow runtime.
See https://www.tensorflow.org/install/errors
for some common reasons and solutions. Include the entire stack trace
above this error message when asking for help.
During handling of the above exception, another exception occurred:
ImportError Traceback (most recent call last)
<ipython-input-37-c947233989bd> in <module>
----> 1 from keras.models import Sequential
2 from keras.layers import Dense
3 from keras.layers import LSTM
~\Anaconda3\envs\ML\lib\site-packages\keras\__init__.py in <module>
4 except ImportError:
5 raise ImportError(
----> 6 'Keras requires TensorFlow 2.2 or higher. '
7 'Install TensorFlow via `pip install tensorflow`')
8
ImportError: Keras requires TensorFlow 2.2 or higher. Install TensorFlow via `pip install tensorflow`
Any help on how to solve this issue and install using anaconda? Thanks in advance
The output of conda list on my environment as follows
(ML) C:\Users\rp603>conda list
# packages in environment at C:\Users\rp603\Anaconda3\envs\ML:
#
# Name Version Build Channel
_tflow_select 2.2.0 eigen
absl-py 0.11.0 py37haa95532_0
aiohttp 3.7.2 py37h2bbff1b_1
alabaster 0.7.12 py37_0
argh 0.26.2 py37_0
argon2-cffi 20.1.0 py37he774522_1
astor 0.8.1 py37_0
astroid 2.4.2 py37_0
async-timeout 3.0.1 py37_0
async_generator 1.10 py37h28b3542_0
atomicwrites 1.4.0 py_0
attrs 20.3.0 pyhd3eb1b0_0
autopep8 1.5.4 py_0
babel 2.8.1 pyhd3eb1b0_0
backcall 0.2.0 py_0
bcrypt 3.2.0 py37he774522_0
blas 1.0 mkl
bleach 3.2.1 py_0
blinker 1.4 py37_0
brotlipy 0.7.0 py37h2bbff1b_1003
ca-certificates 2020.10.14 0
cached-property 1.5.2 pypi_0 pypi
cachetools 4.1.1 py_0
certifi 2020.6.20 pyhd3eb1b0_3
cffi 1.14.3 py37hcd4344a_2
chardet 3.0.4 py37haa95532_1003
click 7.1.2 py_0
cloudpickle 1.6.0 py_0
colorama 0.4.4 py_0
cpuonly 1.0 0 pytorch
cryptography 3.2.1 py37hcd4344a_1
cycler 0.10.0 py37_0
decorator 4.4.2 py_0
defusedxml 0.6.0 py_0
diff-match-patch 20200713 py_0
docutils 0.16 py37_1
entrypoints 0.3 py37_0
flake8 3.8.4 py_0
freetype 2.10.4 hd328e21_0
future 0.18.2 py37_1
gast 0.2.2 py37_0
google-auth 1.23.0 pyhd3eb1b0_0
google-auth-oauthlib 0.4.2 pyhd3eb1b0_2
google-pasta 0.2.0 py_0
gpytorch 1.2.0 py_0 conda-forge
grpcio 1.31.0 py37he7da953_0
h5py 3.1.0 pypi_0 pypi
hdf5 1.10.4 h7ebc959_0
icc_rt 2019.0.0 h0cc432a_1
icu 58.2 ha925a31_3
idna 2.10 py_0
imagesize 1.2.0 py_0
importlib-metadata 2.0.0 py_1
importlib_metadata 2.0.0 1
intel-openmp 2020.2 254
intervaltree 3.1.0 py_0
ipykernel 5.3.4 py37h5ca1d4c_0
ipython 7.19.0 py37hd4e2768_0
ipython_genutils 0.2.0 py37_0
isort 5.6.4 py_0
jedi 0.17.1 py37_0
jinja2 2.11.2 py_0
joblib 0.17.0 py_0
jpeg 9b hb83a4c4_2
jsonschema 3.2.0 py_2
jupyter_client 6.1.7 py_0
jupyter_core 4.6.3 py37_0
jupyterlab_pygments 0.1.2 py_0
keras 2.4.3 pypi_0 pypi
keras-applications 1.0.8 py_1
keras-preprocessing 1.1.0 py_1
keyring 21.4.0 py37_1
kiwisolver 1.3.0 py37hd77b12b_0
lazy-object-proxy 1.4.3 py37he774522_0
libpng 1.6.37 h2a8f88b_0
libprotobuf 3.13.0.1 h200bbdf_0
libsodium 1.0.18 h62dcd97_0
libspatialindex 1.9.3 h33f27b4_0
libtiff 4.1.0 h56a325e_1
libuv 1.40.0 he774522_0
lz4-c 1.9.2 hf4a77e7_3
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
markdown 3.3.3 py37haa95532_0
markupsafe 1.1.1 py37hfa6e2cd_1
matplotlib 3.3.2 0
matplotlib-base 3.3.2 py37hba9282a_0
mccabe 0.6.1 py37_1
mistune 0.8.4 py37hfa6e2cd_1001
mkl 2020.2 256
mkl-service 2.3.0 py37h2bbff1b_0
mkl_fft 1.2.0 py37h45dec08_0
mkl_random 1.1.1 py37h47e9c7a_0
msys2-conda-epoch 20160418 1
multidict 4.7.6 py37he774522_1
nbclient 0.5.1 py_0
nbconvert 6.0.7 py37_0
nbformat 5.0.8 py_0
nest-asyncio 1.4.2 pyhd3eb1b0_0
ninja 1.10.1 py37h7ef1ec2_0
notebook 6.1.4 py37_0
numpy 1.19.4 pypi_0 pypi
numpy-base 1.19.2 py37ha3acd2a_0
numpydoc 1.1.0 pyhd3eb1b0_1
oauthlib 3.1.0 py_0
olefile 0.46 py37_0
openssl 1.1.1h he774522_0
opt_einsum 3.1.0 py_0
packaging 20.4 py_0
pandas 1.1.3 py37ha925a31_0
pandoc 2.11 h9490d1a_0
pandocfilters 1.4.3 py37haa95532_1
paramiko 2.7.2 py_0
parso 0.7.0 py_0
pathtools 0.1.2 py_1
pexpect 4.8.0 pyhd3eb1b0_3
pickleshare 0.7.5 py37_1001
pillow 8.0.1 py37h4fa10fc_0
pip 20.2.4 py37haa95532_0
pluggy 0.13.1 py37_0
prometheus_client 0.8.0 py_0
prompt-toolkit 3.0.8 py_0
protobuf 3.13.0.1 py37ha925a31_1
psutil 5.7.2 py37he774522_0
ptyprocess 0.6.0 pyhd3eb1b0_2
pyasn1 0.4.8 py_0
pyasn1-modules 0.2.8 py_0
pycodestyle 2.6.0 py_0
pycparser 2.20 py_2
pydocstyle 5.1.1 py_0
pyflakes 2.2.0 py_0
pygments 2.7.2 pyhd3eb1b0_0
pyjwt 1.7.1 py37_0
pylint 2.6.0 py37_0
pynacl 1.4.0 py37h62dcd97_1
pyopenssl 19.1.0 pyhd3eb1b0_1
pyparsing 2.4.7 py_0
pyqt 5.9.2 py37h6538335_2
pyreadline 2.1 py37_1
pyrsistent 0.17.3 py37he774522_0
pysocks 1.7.1 py37_1
python 3.7.9 h60c2a47_0
python-dateutil 2.8.1 py_0
python-jsonrpc-server 0.4.0 py_0
python-language-server 0.35.1 py_0
python_abi 3.7 1_cp37m conda-forge
pytorch 1.7.0 py3.7_cpu_0 [cpuonly] pytorch
pytz 2020.1 py_0
pywin32 227 py37he774522_1
pywin32-ctypes 0.2.0 py37_1001
pywinpty 0.5.7 py37_0
pyyaml 5.3.1 pypi_0 pypi
pyzmq 19.0.2 py37ha925a31_1
qdarkstyle 2.8.1 py_0
qt 5.9.7 vc14h73c81de_0
qtawesome 1.0.1 py_0
qtconsole 4.7.7 py_0
qtpy 1.9.0 py_0
requests 2.24.0 py_0
requests-oauthlib 1.3.0 py_0
rope 0.18.0 py_0
rsa 4.6 py_0
rtree 0.9.4 py37h21ff451_1
scikit-learn 0.23.2 py37h47e9c7a_0
scipy 1.4.1 pypi_0 pypi
seaborn 0.11.0 py_0
send2trash 1.5.0 py37_0
setuptools 50.3.1 py37haa95532_1
sip 4.19.8 py37h6538335_0
six 1.15.0 py37haa95532_0
snowballstemmer 2.0.0 py_0
sortedcontainers 2.2.2 py_0
sphinx 3.2.1 py_0
sphinxcontrib-applehelp 1.0.2 py_0
sphinxcontrib-devhelp 1.0.2 py_0
sphinxcontrib-htmlhelp 1.0.3 py_0
sphinxcontrib-jsmath 1.0.1 py_0
sphinxcontrib-qthelp 1.0.3 py_0
sphinxcontrib-serializinghtml 1.1.4 py_0
spyder 4.1.5 py37_0
spyder-kernels 1.9.4 py37_0
sqlite 3.33.0 h2a8f88b_0
tensorboard 2.3.0 pyh4dce500_0
tensorboard-plugin-wit 1.6.0 py_0
tensorflow 2.3.1 pypi_0 pypi
tensorflow-estimator 2.3.0 pypi_0 pypi
termcolor 1.1.0 py37_1
terminado 0.9.1 py37_0
testpath 0.4.4 py_0
threadpoolctl 2.1.0 pyh5ca1d4c_0
tk 8.6.10 he774522_0
toml 0.10.1 py_0
torchaudio 0.7.0 py37 pytorch
torchvision 0.8.1 py37_cpu [cpuonly] pytorch
tornado 6.0.4 py37he774522_1
traitlets 5.0.5 py_0
typed-ast 1.4.1 py37he774522_0
typing-extensions 3.7.4.3 0
typing_extensions 3.7.4.3 py_0
ujson 4.0.1 py37ha925a31_0
urllib3 1.25.11 py_0
vc 14.1 h0510ff6_4
vs2015_runtime 14.16.27012 hf0eaf9b_3
watchdog 0.10.3 py37_0
wcwidth 0.2.5 py_0
webencodings 0.5.1 py37_1
werkzeug 0.14.1 py37_0
wheel 0.35.1 pyhd3eb1b0_0
win_inet_pton 1.1.0 py37haa95532_0
wincertstore 0.2 py37_0
windrose 1.6.8 pyh9f0ad1d_0 conda-forge
winpty 0.4.3 4
wrapt 1.11.2 py37he774522_0
xlrd 1.2.0 pypi_0 pypi
xz 5.2.5 h62dcd97_0
yaml 0.2.5 he774522_0
yapf 0.30.0 py_0
yarl 1.5.1 py37he774522_0
zeromq 4.3.2 ha925a31_3
zipp 3.4.0 pyhd3eb1b0_0
zlib 1.2.11 h62dcd97_4
zstd 1.4.5 h04227a9_0

Your tensorflow is being imported from
File "C:\Users\rp603\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\pywrap_tensorflow.py"
which is a python 3.7 installation that is different from your anaconda one. You are likely seeing issues because of this.
Uninstall any python installation other than the anaconda one, you should not need them anymore. Also remove C:\Users\rp603\AppData\Roaming\Python\Python37 after uninstalling that python version to make sure no residues remain that can cause issues

How can I check if I installed Python, pandas, and Jupyter with conda or pip? Should I reinstall it with conda?

I don't remember how I installed python. I'm learning to use Jupyter now and the official website recommends to install python using conda, not pip.
1) Why is installing python and Jupyter with pip not advisable? I understand the difference between pip and conda, but can someone please explain to me why Jupyter recommends to use conda to install it? Is there a way for me to check how I installed python? Should i reinstall it with conda if I used pip?
2) I'm trying to understand the whole conda is a package installer but also manages venv. typed "list" into the anaconda prompt and it gave me a list that I have some questions about.
(base) C:\Users\ellie>conda list
# packages in environment at C:\Users\ellie\anaconda3:
#
# Name Version Build Channel
_ipyw_jlab_nb_ext_conf 0.1.0 py37_0
alabaster 0.7.12 py37_0
anaconda 2020.02 py37_0
anaconda-client 1.7.2 py37_0
anaconda-navigator 1.9.12 py37_0
anaconda-project 0.8.4 py_0
appdirs 1.4.3 pypi_0 pypi
argh 0.26.2 py37_0
asn1crypto 1.3.0 py37_0
astroid 2.3.3 py37_0
astropy 4.0 py37he774522_0
atomicwrites 1.3.0 py37_1
attrs 19.3.0 py_0
autopep8 1.4.4 py_0
babel 2.8.0 py_0
backcall 0.1.0 py37_0
backports 1.0 py_2
backports.functools_lru_cache 1.6.1 py_0
backports.shutil_get_terminal_size 1.0.0 py37_2
backports.tempfile 1.0 py_1
backports.weakref 1.0.post1 py_1
bcrypt 3.1.7 py37he774522_0
beautifulsoup4 4.8.2 py37_0
bitarray 1.2.1 py37he774522_0
bkcharts 0.2 py37_0
blas 1.0 mkl
bleach 3.1.0 py37_0
blosc 1.16.3 h7bd577a_0
bokeh 1.4.0 py37_0
boto 2.49.0 py37_0
bottleneck 1.3.2 py37h2a96729_0
bzip2 1.0.8 he774522_0
ca-certificates 2020.1.1 0
certifi 2019.11.28 py37_0
cffi 1.14.0 py37h7a1dbc1_0
chardet 3.0.4 py37_1003
click 7.0 py37_0
cloudpickle 1.3.0 py_0
clyent 1.2.2 py37_1
colorama 0.4.3 py_0
comtypes 1.1.7 py37_0
conda 4.8.2 py37_0
conda-build 3.18.11 py37_0
conda-env 2.6.0 1
conda-package-handling 1.6.0 py37h62dcd97_0
conda-verify 3.4.2 py_1
console_shortcut 0.1.1 4
contextlib2 0.6.0.post1 py_0
cryptography 2.8 py37h7a1dbc1_0
curl 7.68.0 h2a8f88b_0
cycler 0.10.0 py37_0
cython 0.29.15 py37ha925a31_0
cytoolz 0.10.1 py37he774522_0
dask 2.11.0 py_0
dask-core 2.11.0 py_0
decorator 4.4.1 py_0
defusedxml 0.6.0 py_0
diff-match-patch 20181111 py_0
distlib 0.3.0 pypi_0 pypi
distributed 2.11.0 py37_0
docutils 0.16 py37_0
entrypoints 0.3 py37_0
et_xmlfile 1.0.1 py37_0
fastcache 1.1.0 py37he774522_0
filelock 3.0.12 py_0
flake8 3.7.9 py37_0
flask 1.1.1 py_0
freetype 2.9.1 ha9979f8_1
fsspec 0.6.2 py_0
future 0.18.2 py37_0
get_terminal_size 1.0.0 h38e98db_0
gevent 1.4.0 py37he774522_0
glob2 0.7 py_0
greenlet 0.4.15 py37hfa6e2cd_0
h5py 2.10.0 py37h5e291fa_0
hdf5 1.10.4 h7ebc959_0
heapdict 1.0.1 py_0
html5lib 1.0.1 py37_0
hypothesis 5.5.4 py_0
icc_rt 2019.0.0 h0cc432a_1
icu 58.2 ha66f8fd_1
idna 2.8 py37_0
imageio 2.6.1 py37_0
imagesize 1.2.0 py_0
importlib_metadata 1.5.0 py37_0
intel-openmp 2020.0 166
intervaltree 3.0.2 py_0
ipykernel 5.1.4 py37h39e3cac_0
ipython 7.12.0 py37h5ca1d4c_0
ipython_genutils 0.2.0 py37_0
ipywidgets 7.5.1 py_0
isort 4.3.21 py37_0
itsdangerous 1.1.0 py37_0
jdcal 1.4.1 py_0
jedi 0.14.1 py37_0
jinja2 2.11.1 py_0
joblib 0.14.1 py_0
jpeg 9b hb83a4c4_2
json5 0.9.1 py_0
jsonschema 3.2.0 py37_0
jupyter 1.0.0 py37_7
jupyter_client 5.3.4 py37_0
jupyter_console 6.1.0 py_0
jupyter_core 4.6.1 py37_0
jupyterlab 1.2.6 pyhf63ae98_0
jupyterlab_server 1.0.6 py_0
keyring 21.1.0 py37_0
kiwisolver 1.1.0 py37ha925a31_0
krb5 1.17.1 hc04afaa_0
lazy-object-proxy 1.4.3 py37he774522_0
libarchive 3.3.3 h0643e63_5
libcurl 7.68.0 h2a8f88b_0
libiconv 1.15 h1df5818_7
liblief 0.9.0 ha925a31_2
libpng 1.6.37 h2a8f88b_0
libsodium 1.0.16 h9d3ae62_0
libspatialindex 1.9.3 h33f27b4_0
libssh2 1.8.2 h7a1dbc1_0
libtiff 4.1.0 h56a325e_0
libxml2 2.9.9 h464c3ec_0
libxslt 1.1.33 h579f668_0
llvmlite 0.31.0 py37ha925a31_0
locket 0.2.0 py37_1
lxml 4.5.0 py37h1350720_0
lz4-c 1.8.1.2 h2fa13f4_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 1.1.1 py37he774522_0
matplotlib 3.2.1 pypi_0 pypi
mccabe 0.6.1 py37_1
menuinst 1.4.16 py37he774522_0
mistune 0.8.4 py37he774522_0
mkl 2020.0 166
mkl-service 2.3.0 py37hb782905_0
mkl_fft 1.0.15 py37h14836fe_0
mkl_random 1.1.0 py37h675688f_0
mock 4.0.1 py_0
more-itertools 8.2.0 py_0
mpmath 1.1.0 py37_0
msgpack-python 0.6.1 py37h74a9793_1
msys2-conda-epoch 20160418 1
multipledispatch 0.6.0 py37_0
navigator-updater 0.2.1 py37_0
nbconvert 5.6.1 py37_0
nbformat 5.0.4 py_0
networkx 2.4 py_0
nltk 3.4.5 py37_0
nose 1.3.7 py37_2
notebook 6.0.3 py37_0
numba 0.48.0 py37h47e9c7a_0
numexpr 2.7.1 py37h25d0782_0
numpy 1.18.1 py37h93ca92e_0
numpy-base 1.18.1 py37hc3f5095_1
numpydoc 0.9.2 py_0
olefile 0.46 py37_0
openpyxl 3.0.3 py_0
openssl 1.1.1d he774522_4
packaging 20.1 py_0
pandas 1.0.1 py37h47e9c7a_0
pandoc 2.2.3.2 0
pandocfilters 1.4.2 py37_1
paramiko 2.7.1 py_0
parso 0.5.2 py_0
partd 1.1.0 py_0
path 13.1.0 py37_0
path.py 12.4.0 0
pathlib2 2.3.5 py37_0
pathtools 0.1.2 py_1
patsy 0.5.1 py37_0
pep8 1.7.1 py37_0
pexpect 4.8.0 py37_0
pickleshare 0.7.5 py37_0
pillow 7.0.0 py37hcc1f983_0
pip 20.0.2 py37_1
pkginfo 1.5.0.1 py37_0
pluggy 0.13.1 py37_0
ply 3.11 py37_0
powershell_shortcut 0.0.1 3
prometheus_client 0.7.1 py_0
prompt_toolkit 3.0.3 py_0
psutil 5.6.7 py37he774522_0
py 1.8.1 py_0
py-lief 0.9.0 py37ha925a31_2
pycodestyle 2.5.0 py37_0
pycosat 0.6.3 py37he774522_0
pycparser 2.19 py37_0
pycrypto 2.6.1 py37hfa6e2cd_9
pycurl 7.43.0.5 py37h7a1dbc1_0
pydocstyle 4.0.1 py_0
pyflakes 2.1.1 py37_0
pygments 2.5.2 py_0
pyjwt 1.7.1 pypi_0 pypi
pylint 2.4.4 py37_0
pynacl 1.3.0 py37h62dcd97_0
pyodbc 4.0.30 py37ha925a31_0
pyopenssl 19.1.0 py37_0
pyparsing 2.4.6 py_0
pyqt 5.9.2 py37h6538335_2
pyreadline 2.1 py37_1
pyrsistent 0.15.7 py37he774522_0
pysocks 1.7.1 py37_0
pytables 3.6.1 py37h1da0976_0
pytest 5.3.5 py37_0
pytest-arraydiff 0.3 py37h39e3cac_0
pytest-astropy 0.8.0 py_0
pytest-astropy-header 0.1.2 py_0
pytest-doctestplus 0.5.0 py_0
pytest-openfiles 0.4.0 py_0
pytest-remotedata 0.3.2 py37_0
python 3.7.6 h60c2a47_2
python-dateutil 2.8.1 py_0
python-jsonrpc-server 0.3.4 py_0
python-language-server 0.31.7 py37_0
python-libarchive-c 2.8 py37_13
pytz 2019.3 py_0
pywavelets 1.1.1 py37he774522_0
pywin32 227 py37he774522_1
pywin32-ctypes 0.2.0 py37_1000
pywinpty 0.5.7 py37_0
pyyaml 5.3 py37he774522_0
pyzmq 18.1.1 py37ha925a31_0
qdarkstyle 2.8 py_0
qt 5.9.7 vc14h73c81de_0
qtawesome 0.6.1 py_0
qtconsole 4.6.0 py_1
qtpy 1.9.0 py_0
requests 2.22.0 py37_1
rope 0.16.0 py_0
rtree 0.9.3 py37h21ff451_0
ruamel_yaml 0.15.87 py37he774522_0
scikit-image 0.16.2 py37h47e9c7a_0
scikit-learn 0.22.1 py37h6288b17_0
scipy 1.4.1 py37h9439919_0
seaborn 0.10.0 py_0
send2trash 1.5.0 py37_0
setuptools 45.2.0 py37_0
simplegeneric 0.8.1 py37_2
singledispatch 3.4.0.3 py37_0
sip 4.19.8 py37h6538335_0
six 1.14.0 py37_0
snappy 1.1.7 h777316e_3
snowballstemmer 2.0.0 py_0
sortedcollections 1.1.2 py37_0
sortedcontainers 2.1.0 py37_0
soupsieve 1.9.5 py37_0
sphinx 2.4.0 py_0
sphinxcontrib 1.0 py37_1
sphinxcontrib-applehelp 1.0.1 py_0
sphinxcontrib-devhelp 1.0.1 py_0
sphinxcontrib-htmlhelp 1.0.2 py_0
sphinxcontrib-jsmath 1.0.1 py_0
sphinxcontrib-qthelp 1.0.2 py_0
sphinxcontrib-serializinghtml 1.1.3 py_0
sphinxcontrib-websupport 1.2.0 py_0
spyder 4.0.1 py37_0
spyder-kernels 1.8.1 py37_0
sqlalchemy 1.3.13 py37he774522_0
sqlite 3.31.1 he774522_0
statsmodels 0.11.0 py37he774522_0
sympy 1.5.1 py37_0
tbb 2020.0 h74a9793_0
tblib 1.6.0 py_0
terminado 0.8.3 py37_0
testpath 0.4.4 py_0
tk 8.6.8 hfa6e2cd_0
toolz 0.10.0 py_0
tornado 6.0.3 py37he774522_3
tqdm 4.42.1 py_0
traitlets 4.3.3 py37_0
twilio 6.39.0 pypi_0 pypi
ujson 1.35 py37hfa6e2cd_0
unicodecsv 0.14.1 py37_0
urllib3 1.25.8 py37_0
vc 14.1 h0510ff6_4
virtualenv 20.0.16 pypi_0 pypi
vs2015_runtime 14.16.27012 hf0eaf9b_1
watchdog 0.10.2 py37_0
wcwidth 0.1.8 py_0
webencodings 0.5.1 py37_1
werkzeug 1.0.0 py_0
wheel 0.34.2 py37_0
widgetsnbextension 3.5.1 py37_0
win_inet_pton 1.1.0 py37_0
win_unicode_console 0.5 py37_0
wincertstore 0.2 py37_0
winpty 0.4.3 4
wrapt 1.11.2 py37he774522_0
xlrd 1.2.0 py37_0
xlsxwriter 1.2.7 py_0
xlwings 0.17.1 py37_0
xlwt 1.3.0 py37_0
xmltodict 0.12.0 py_0
xz 5.2.4 h2fa13f4_4
yaml 0.1.7 hc54c509_2
yapf 0.28.0 py_0
zeromq 4.3.1 h33f27b4_3
zict 1.0.0 py_0
zipp 2.2.0 py_0
zlib 1.2.11 h62dcd97_3
zstd 1.3.7 h508b16e_0
(base) C:\Users\ellie>
2.1) does this show me a list of all my packages or just the packages i installed with conda?
2.2) according to conda.io, "Conda channels are the locations where packages are stored". What is a "pypi" location? How is that a location? Also, it says at the top that everything is stored at C:\Users\ellie\anaconda3:. So how is a channel different from the C:\Users\ellie\anaconda3: lcoation?
3) Is there a downside to moving the default jupyter notebook location to somewhere other than the C drive? / Is anyone else's jupyter home directory (http://localhost:8888/tree) filled with garbage like a desktop folder and some shit you installed 80 years ago? None of the tutorial people have their entire lives in their tree directory, so this makes me wonder where I went wrong. I'm sorry that this is the dumbest question ever. Is there a reason Jupyter made a folder with a bunch of garbage in it my home directory? Is there a downside to moving my home directory to the D drive?

1)
Installing Anaconda encompasses python and the conda package manager. Anaconda is a tool, or framework, containing very many useful tools and programs to work with (big) data.
I believe the reason Jupyter wants you to use conda, is to make sure the dependencies are already installed, and the fact that it is mainly developed for the Anaconda environment.
Speaking of venv, the reason it is installed is that Anaconda also functions as a environment manager, letting you choose your installed packages and versions. For example, you could create an environment which uses python2, and install only python2 libraries in it, without changing the root environment.
If you used pip to install python, i recommend just installing Anaconda as a whole.
Jupyter without Anaconda is also feasible, but does not nearly have the same amount of support and frameworks, and fiddling with the jupyter-libs is not something that pays off (trust me, I tried myself).
The bottom line is that pip gives you more freedom in what you want to install, but conda is easier to use and recommended for data-driven programming. They can co-exist without a problem (except maybe some problems with your path, which should be really easy to fix, judging by the amount of questions about this topic on StackOverflow.).
I personally use Jupyter strictly with Anaconda, because it lets me switch between projects on-the-fly without worrying about having the right dependencies available, and it lets me use JupyterHub, which is a big plus in my book. Also, it spares me the hassle of fiddling with the jupyter versions, which can be a real pain.
2.1)
These are all packages that either were shipped with conda, or you yourself installed with conda. However, if you want to be sure, you can check your pip packages by running pip list. Your pip packages should be stored somewhere else on your machine, so your python installs do not get in each other's way. Thankfully, this is the default.
2.2)
Channels are NOT a location on your drive, they are locations on the conda cloud. If conda looks for a package to install, it iterates through a hierarchy of channels, until it finds your requested package or finds nothing on any channel. You can to some extent
control this hierarchy, but as a beginner it is not important. The channels that are important, however, are those that are given by your operating system; if you use Windows, only packages are found that are explicitly availiable for the Windows operating systems. These packages, in turn, are organized in a channel, mostly named after your os. These packages are then installed on your drive in a folder with the same name as the channel, so conda can keep track of the different packages you have installed for different os's.
2.3)
It is possible (and recommended) that you start your Jupyter Notebook in the respective folder, either by using jupyter notebook --notebook-dir '<your folder>' or by changing the jupyter start folder.
On a sidenote, most of the questions you asked here are already answered on this site, and with a little digging you could have answered most of these questions beforehand.
Nevertheless, i am not a Anaconda pro myself, and channels are a concept that somebody else might elaborate on some more.

How do I install the most recent Tensorflow (here: 2.2) on Windows when conda does not yet support it?

I have conda 4.8.3 and Python 3.7.4 on Windows 8.1.
I have tf 2.0.0 installed in a conda environment. How do I upgrade to 2.2.x?
Or, how do I just install 2.2.x in a conda environment?
Edit 1: pip install --upgrade tensorflow says: Requirement already up-to-date: tensorflow in d:\anaconda3\envs\tf2\lib\site-packages (2.1.0)
but tf version is still 2.0.
Edit 2: conda install tensorflow==2.2.0 says:
PackagesNotFoundError: The following packages are not available from current channels:
tensorflow==2.2.0
I did have some luck here.
Edit 3:
(tf2) D:\ray\dev\covid-19>conda list -n tf2
# packages in environment at D:\Anaconda3\envs\tf2:
#
# Name Version Build Channel
_anaconda_depends 2019.03 py37_0
_ipyw_jlab_nb_ext_conf 0.1.0 py37_0
_tflow_select 2.3.0 mkl
absl-py 0.9.0 pypi_0 pypi
alabaster 0.7.12 py37_0
anaconda custom py37_1
anaconda-client 1.7.2 py37_0
anaconda-navigator 1.9.7 py37_0
anaconda-project 0.8.3 py_0
asn1crypto 1.0.1 py37_0
astor 0.8.1 pypi_0 pypi
astroid 2.3.1 py37_0
astropy 3.2.1 py37he774522_0
atomicwrites 1.3.0 py37_1
attrs 19.2.0 py_0
babel 2.7.0 py_0
backcall 0.1.0 py37_0
backports 1.0 py_2
backports.functools_lru_cache 1.5 py_2
backports.os 0.1.1 py37_0
backports.shutil_get_terminal_size 1.0.0 py37_2
backports.tempfile 1.0 py_1
backports.weakref 1.0.post1 py_1
beautifulsoup4 4.8.0 py37_0
bitarray 1.0.1 py37he774522_0
bkcharts 0.2 py37_0
blas 1.0 mkl
bleach 3.1.0 py37_0
blosc 1.16.3 h7bd577a_0
bokeh 1.3.4 py37_0
boto 2.49.0 py37_0
bottleneck 1.2.1 py37h452e1ab_1
bzip2 1.0.8 he774522_0
ca-certificates 2020.1.1 0
cachetools 4.0.0 pypi_0 pypi
certifi 2019.9.11 py37_0
cffi 1.12.3 py37h7a1dbc1_0
chardet 3.0.4 py37_1003
click 7.0 py37_0
cloudpickle 1.2.2 py_0
clyent 1.2.2 py37_1
colorama 0.4.1 py37_0
comtypes 1.1.7 py37_0
conda-package-handling 1.6.0 py37h62dcd97_0
conda-verify 3.4.2 py_1
console_shortcut 0.1.1 3
contextlib2 0.6.0 py_0
cryptography 2.7 py37h7a1dbc1_0
curl 7.65.3 h2a8f88b_0
cycler 0.10.0 py37_0
cython 0.29.13 py37ha925a31_0
cytoolz 0.10.0 py37he774522_0
dask 2.5.2 py_0
dask-core 2.5.2 py_0
decorator 4.4.0 py37_1
defusedxml 0.6.0 py_0
dill 0.3.1.1 pypi_0 pypi
distributed 2.5.2 py_0
docutils 0.15.2 py37_0
entrypoints 0.3 py37_0
et_xmlfile 1.0.1 py37_0
fastcache 1.1.0 py37he774522_0
filelock 3.0.12 py_0
flask 1.1.1 py_0
freetype 2.9.1 ha9979f8_1
fsspec 0.5.2 py_0
future 0.17.1 py37_0
gast 0.2.2 pypi_0 pypi
get_terminal_size 1.0.0 h38e98db_0
gevent 1.4.0 py37he774522_0
glob2 0.7 py_0
google-auth 1.11.0 pypi_0 pypi
google-auth-oauthlib 0.4.1 pypi_0 pypi
google-pasta 0.1.8 py_0
googleapis-common-protos 1.51.0 pypi_0 pypi
greenlet 0.4.15 py37hfa6e2cd_0
grpcio 1.26.0 pypi_0 pypi
h5py 2.9.0 py37h5e291fa_0
hdf5 1.10.4 h7ebc959_0
heapdict 1.0.1 py_0
html5lib 1.0.1 py37_0
icc_rt 2019.0.0 h0cc432a_1
icu 58.2 ha66f8fd_1
idna 2.8 py37_0
imageio 2.6.0 py37_0
imagesize 1.1.0 py37_0
importlib_metadata 0.23 py37_0
intel-openmp 2019.4 245
ipykernel 5.1.2 py37h39e3cac_0
ipython 7.8.0 py37h39e3cac_0
ipython_genutils 0.2.0 py37_0
ipywidgets 7.5.1 py_0
isort 4.3.21 py37_0
itsdangerous 1.1.0 py37_0
jdcal 1.4.1 py_0
jedi 0.15.1 py37_0
jinja2 2.10.3 py_0
joblib 0.13.2 py37_0
jpeg 9b hb83a4c4_2
json5 0.8.5 py_0
jsonschema 3.0.2 py37_0
jupyter 1.0.0 py37_7
jupyter_client 5.3.3 py37_1
jupyter_console 6.0.0 py37_0
jupyter_core 4.5.0 py_0
jupyterlab 1.1.4 pyhf63ae98_0
jupyterlab_server 1.0.6 py_0
keras 2.3.1 py37h21ff451_0 conda-forge
keras-applications 1.0.8 py_0
keras-preprocessing 1.1.0 py_1
keyring 18.0.0 py37_0
kiwisolver 1.1.0 py37ha925a31_0
krb5 1.16.1 hc04afaa_7
lazy-object-proxy 1.4.2 py37he774522_0
libarchive 3.3.3 h0643e63_5
libcurl 7.65.3 h2a8f88b_0
libgpuarray 0.7.6 hfa6e2cd_0
libiconv 1.15 h1df5818_7
liblief 0.9.0 ha925a31_2
libmklml 2019.0.5 0
libpng 1.6.37 h2a8f88b_0
libprotobuf 3.11.2 h7bd577a_0
libpython 2.1 py37_0
libsodium 1.0.16 h9d3ae62_0
libssh2 1.8.2 h7a1dbc1_0
libtiff 4.0.10 hb898794_2
libxml2 2.9.9 h464c3ec_0
libxslt 1.1.33 h579f668_0
llvmlite 0.29.0 py37ha925a31_0
locket 0.2.0 py37_1
lxml 4.4.1 py37h1350720_0
lz4-c 1.8.1.2 h2fa13f4_0
lzo 2.10 h6df0209_2
m2w64-binutils 2.25.1 5
m2w64-bzip2 1.0.6 6
m2w64-crt-git 5.0.0.4636.2595836 2
m2w64-gcc 5.3.0 6
m2w64-gcc-ada 5.3.0 6
m2w64-gcc-fortran 5.3.0 6
m2w64-gcc-libgfortran 5.3.0 6
m2w64-gcc-libs 5.3.0 7
m2w64-gcc-libs-core 5.3.0 7
m2w64-gcc-objc 5.3.0 6
m2w64-gmp 6.1.0 2
m2w64-headers-git 5.0.0.4636.c0ad18a 2
m2w64-isl 0.16.1 2
m2w64-libiconv 1.14 6
m2w64-libmangle-git 5.0.0.4509.2e5a9a2 2
m2w64-libwinpthread-git 5.0.0.4634.697f757 2
m2w64-make 4.1.2351.a80a8b8 2
m2w64-mpc 1.0.3 3
m2w64-mpfr 3.1.4 4
m2w64-pkg-config 0.29.1 2
m2w64-toolchain 5.3.0 7
m2w64-tools-git 5.0.0.4592.90b8472 2
m2w64-windows-default-manifest 6.4 3
m2w64-winpthreads-git 5.0.0.4634.697f757 2
m2w64-zlib 1.2.8 10
mako 1.1.0 py_0
markdown 3.1.1 py37_0
markupsafe 1.1.1 py37he774522_0
matplotlib 3.1.1 py37hc8f65d3_0
mccabe 0.6.1 py37_1
menuinst 1.4.16 py37he774522_0
mistune 0.8.4 py37he774522_0
mkl 2019.4 245
mkl-service 2.3.0 py37hb782905_0
mkl_fft 1.0.14 py37h14836fe_0
mkl_random 1.1.0 py37h675688f_0
mock 3.0.5 py37_0
more-itertools 7.2.0 py37_0
mpmath 1.1.0 py37_0
msgpack-python 0.6.1 py37h74a9793_1
msys2-conda-epoch 20160418 1
multipledispatch 0.6.0 py37_0
navigator-updater 0.2.1 py37_0
nbconvert 5.6.0 py37_1
nbformat 4.4.0 py37_0
networkx 2.3 py_0
nltk 3.4.5 py37_0
nose 1.3.7 py37_2
notebook 6.0.1 py37_0
numba 0.45.1 py37hf9181ef_0
numexpr 2.7.0 py37hdce8814_0
numpy 1.16.5 py37h19fb1c0_0
numpy-base 1.16.5 py37hc3f5095_0
numpydoc 0.9.1 py_0
oauthlib 3.1.0 pypi_0 pypi
olefile 0.46 py37_0
openpyxl 3.0.0 py_0
openssl 1.1.1d he774522_3
opt_einsum 3.1.0 py_0
packaging 19.2 py_0
pandas 0.25.1 pypi_0 pypi
pandoc 2.2.3.2 0
pandocfilters 1.4.2 py37_1
parso 0.5.1 py_0
partd 1.0.0 py_0
path.py 12.0.1 py_0
pathlib2 2.3.5 py37_0
patsy 0.5.1 py37_0
pep8 1.7.1 py37_0
pickleshare 0.7.5 py37_0
pillow 6.2.0 py37hdc69c19_0
pip 20.0.2 pypi_0 pypi
pkginfo 1.5.0.1 py37_0
pluggy 0.13.0 py37_0
ply 3.11 py37_0
powershell_shortcut 0.0.1 2
prometheus_client 0.7.1 py_0
promise 2.3 pypi_0 pypi
prompt_toolkit 2.0.10 py_0
protobuf 3.11.2 pypi_0 pypi
psutil 5.6.3 py37he774522_0
py 1.8.0 py37_0
py-lief 0.9.0 py37ha925a31_2
pyasn1 0.4.8 pypi_0 pypi
pyasn1-modules 0.2.8 pypi_0 pypi
pycodestyle 2.5.0 py37_0
pycosat 0.6.3 py37hfa6e2cd_0
pycparser 2.19 py37_0
pycrypto 2.6.1 py37hfa6e2cd_9
pycurl 7.43.0.3 py37h7a1dbc1_0
pyflakes 2.1.1 py37_0
pygments 2.4.2 py_0
pygpu 0.7.6 py37h452e1ab_0
pylint 2.4.2 py37_0
pyodbc 4.0.27 py37ha925a31_0
pyopenssl 19.0.0 py37_0
pyparsing 2.4.2 py_0
pyqt 5.9.2 py37h6538335_2
pyreadline 2.1 py37_1
pyrsistent 0.15.4 py37he774522_0
pysocks 1.7.1 py37_0
pytables 3.5.2 py37h1da0976_1
pytest 5.2.1 py37_0
pytest-arraydiff 0.3 py37h39e3cac_0
pytest-astropy 0.5.0 py37_0
pytest-doctestplus 0.4.0 py_0
pytest-openfiles 0.4.0 py_0
pytest-remotedata 0.3.2 py37_0
python 3.7.4 h5263a28_0
python-dateutil 2.8.0 py37_0
python-libarchive-c 2.8 py37_13
pytz 2019.3 py_0
pywavelets 1.0.3 py37h8c2d366_1
pywin32 223 py37hfa6e2cd_1
pywinpty 0.5.5 py37_1000
pyyaml 5.1.2 py37he774522_0
pyzmq 18.1.0 py37ha925a31_0
qt 5.9.7 vc14h73c81de_0
qtawesome 0.6.0 py_0
qtconsole 4.5.5 py_0
qtpy 1.9.0 py_0
requests 2.22.0 py37_0
requests-oauthlib 1.3.0 pypi_0 pypi
rope 0.14.0 py_0
rsa 4.0 pypi_0 pypi
ruamel_yaml 0.15.46 py37hfa6e2cd_0
scikit-image 0.15.0 py37ha925a31_0
scikit-learn 0.21.3 py37h6288b17_0
scipy 1.4.1 pypi_0 pypi
seaborn 0.9.0 py37_0
send2trash 1.5.0 py37_0
setuptools 41.4.0 py37_0
simplegeneric 0.8.1 py37_2
singledispatch 3.4.0.3 py37_0
sip 4.19.8 py37h6538335_0
six 1.12.0 py37_0
sklearn 0.0 pypi_0 pypi
snappy 1.1.7 h777316e_3
snowballstemmer 2.0.0 py_0
sortedcollections 1.1.2 py37_0
sortedcontainers 2.1.0 py37_0
soupsieve 1.9.3 py37_0
sphinx 2.2.0 py_0
sphinxcontrib 1.0 py37_1
sphinxcontrib-applehelp 1.0.1 py_0
sphinxcontrib-devhelp 1.0.1 py_0
sphinxcontrib-htmlhelp 1.0.2 py_0
sphinxcontrib-jsmath 1.0.1 py_0
sphinxcontrib-qthelp 1.0.2 py_0
sphinxcontrib-serializinghtml 1.1.3 py_0
sphinxcontrib-websupport 1.1.2 py_0
spyder 3.3.6 py37_0
spyder-kernels 0.5.2 py37_0
sqlalchemy 1.3.9 py37he774522_0
sqlite 3.30.0 he774522_0
statsmodels 0.10.1 py37h8c2d366_0
sympy 1.4 py37_0
tbb 2019.4 h74a9793_0
tblib 1.4.0 py_0
tensorboard 2.1.0 pypi_0 pypi
tensorflow 2.1.0 pypi_0 pypi
tensorflow-base 2.0.0 mkl_py37hd1d5974_0
tensorflow-datasets 2.0.0 pypi_0 pypi
tensorflow-estimator 2.1.0 pypi_0 pypi
tensorflow-metadata 0.21.1 pypi_0 pypi
termcolor 1.1.0 pypi_0 pypi
terminado 0.8.2 py37_0
testpath 0.4.2 py37_0
theano 1.0.4 py37_0
tk 8.6.8 hfa6e2cd_0
toolz 0.10.0 py_0
tornado 6.0.3 py37he774522_0
tqdm 4.36.1 py_0
traitlets 4.3.3 py37_0
unicodecsv 0.14.1 py37_0
urllib3 1.24.2 py37_0
vc 14.1 h0510ff6_4
vs2015_runtime 14.16.27012 hf0eaf9b_0
wcwidth 0.1.7 py37_0
webencodings 0.5.1 py37_1
werkzeug 0.16.0 py_0
wheel 0.33.6 py37_0
widgetsnbextension 3.5.1 py37_0
win_inet_pton 1.1.0 py37_0
win_unicode_console 0.5 py37_0
wincertstore 0.2 py37_0
winpty 0.4.3 4
wrapt 1.11.2 py37he774522_0
xlrd 1.2.0 py37_0
xlsxwriter 1.2.1 py_0
xlwings 0.15.10 py37_0
xlwt 1.3.0 py37_0
xz 5.2.4 h2fa13f4_4
yaml 0.1.7 hc54c509_2
zeromq 4.3.1 h33f27b4_3
zict 1.0.0 py_0
zipp 0.6.0 py_0
zlib 1.2.11 h62dcd97_3
zstd 1.3.7 h508b16e_0

TF 2.2.0 isn't available on conda yet.

It's possible to install TF 2.2.0 now with either:
pip install tensorflow-gpu==2.2.0
or
pip install https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.2.0-cp37-cp37m-win_amd64.whl
ONE IMPORTANT THING: for now, at least in my case, there is a major problem with the GPU version. The old one recognises my GPU with no issues, while the latest doesn't see it for some reason. I advise you to create, just in case, a new env so you won't need to reinstall everything later on.
EDIT by a reader:
Better do not use pip install at all if you can wait for the conda version to catch up. Using the pip installer is not recommended, even if it often offers a more recent version. Using pip will risk exactly the documented error here. And you do not need to create a new env with conda update, conda update --all will not harm your dependencies in your env. See Why using Anaconda environments to install tensorflow on Windows?.

There are two methods
1. Install into virtual environment with
pip TensorFlow
virtualenv --system-site-packages -p python3 ./venv
then you need to activate your new environment
pip install --upgrade pip
pip list # show packages installed within the virtual environment
this command for quit
deactivate # don't exit until you're done using TensorFlow
we finish by installing tensor
pip install --upgrade tensorflow
2. Install in your system
python3 --version
pip3 --version
virtualenv --version
Ubuntu
sudo apt update
sudo apt install python3-dev python3-pip
sudo pip3 install -U virtualenv # system-wide install
then
pip3 install --user --upgrade tensorflow # install in $HOME

create new environment and use this command in jupyter notebook :
!pip install tensorflow==2.2-rc3
this version work on CPU or GPU.

Its becasue your required tensorflow version is not available in you current python version.
For Example: python 3.9 doesn't has tensorflow 2.2.0
I have faced this issue once, may this helps you.
Thanks