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conda install matplotlib

Collecting package metadata (current_repodata.json): ...working... done
Solving environment: ...working... done

## Package Plan ##

  environment location: C:\Users\369rental\anaconda3\envs\jupyter

  added / updated specs:
    - matplotlib


The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    contourpy-1.2.0            |  py311h59b6b97_0         218 KB
    icu-73.1                   |       h6c2663c_0        29.5 MB
    intel-openmp-2023.1.0      |   h59b6b97_46320         2.7 MB
    libdeflate-1.17            |       h2bbff1b_1         153 KB
    matplotlib-3.8.0           |  py311haa95532_0           9 KB
    matplotlib-base-3.8.0      |  py311hf62ec03_0         7.6 MB
    mkl-2023.1.0               |   h6b88ed4_46358       155.9 MB
    numpy-1.26.3               |  py311hdab7c0b_0          11 KB
    numpy-base-1.26.3          |  py311hd01c5d8_0         7.3 MB
    pillow-10.0.1              |  py311h045eedc_0         937 KB
    pyqt-5.15.10               |  py311hd77b12b_0         4.1 MB
    pyqt5-sip-12.13.0          |  py311h2bbff1b_0          75 KB
    qt-main-5.15.2             |      h19c9488_10        59.4 MB
    sip-6.7.12                 |  py311hd77b12b_0         615 KB
    ------------------------------------------------------------
                                           Total:       268.4 MB

The following NEW packages will be INSTALLED:

  blas               pkgs/main/win-64::blas-1.0-mkl 
  brotli             pkgs/main/win-64::brotli-1.0.9-h2bbff1b_7 
  brotli-bin         pkgs/main/win-64::brotli-bin-1.0.9-h2bbff1b_7 
  contourpy          pkgs/main/win-64::contourpy-1.2.0-py311h59b6b97_0 
  cycler             pkgs/main/noarch::cycler-0.11.0-pyhd3eb1b0_0 
  fonttools          pkgs/main/noarch::fonttools-4.25.0-pyhd3eb1b0_0 
  freetype           pkgs/main/win-64::freetype-2.12.1-ha860e81_0 
  giflib             pkgs/main/win-64::giflib-5.2.1-h8cc25b3_3 
  icu                pkgs/main/win-64::icu-73.1-h6c2663c_0 
  intel-openmp       pkgs/main/win-64::intel-openmp-2023.1.0-h59b6b97_46320 
  jpeg               pkgs/main/win-64::jpeg-9e-h2bbff1b_1 
  kiwisolver         pkgs/main/win-64::kiwisolver-1.4.4-py311hd77b12b_0 
  krb5               pkgs/main/win-64::krb5-1.20.1-h5b6d351_0 
  lerc               pkgs/main/win-64::lerc-3.0-hd77b12b_0 
  libbrotlicommon    pkgs/main/win-64::libbrotlicommon-1.0.9-h2bbff1b_7 
  libbrotlidec       pkgs/main/win-64::libbrotlidec-1.0.9-h2bbff1b_7 
  libbrotlienc       pkgs/main/win-64::libbrotlienc-1.0.9-h2bbff1b_7 
  libclang           pkgs/main/win-64::libclang-14.0.6-default_hb5a9fac_1 
  libclang13         pkgs/main/win-64::libclang13-14.0.6-default_h8e68704_1 
  libdeflate         pkgs/main/win-64::libdeflate-1.17-h2bbff1b_1 
  libpng             pkgs/main/win-64::libpng-1.6.39-h8cc25b3_0 
  libpq              pkgs/main/win-64::libpq-12.15-h906ac69_1 
  libtiff            pkgs/main/win-64::libtiff-4.5.1-hd77b12b_0 
  libwebp            pkgs/main/win-64::libwebp-1.3.2-hbc33d0d_0 
  libwebp-base       pkgs/main/win-64::libwebp-base-1.3.2-h2bbff1b_0 
  lz4-c              pkgs/main/win-64::lz4-c-1.9.4-h2bbff1b_0 
  matplotlib         pkgs/main/win-64::matplotlib-3.8.0-py311haa95532_0 
  matplotlib-base    pkgs/main/win-64::matplotlib-base-3.8.0-py311hf62ec03_0 
  mkl                pkgs/main/win-64::mkl-2023.1.0-h6b88ed4_46358 
  mkl-service        pkgs/main/win-64::mkl-service-2.4.0-py311h2bbff1b_1 
  mkl_fft            pkgs/main/win-64::mkl_fft-1.3.8-py311h2bbff1b_0 
  mkl_random         pkgs/main/win-64::mkl_random-1.2.4-py311h59b6b97_0 
  munkres            pkgs/main/noarch::munkres-1.1.4-py_0 
  numpy              pkgs/main/win-64::numpy-1.26.3-py311hdab7c0b_0 
  numpy-base         pkgs/main/win-64::numpy-base-1.26.3-py311hd01c5d8_0 
  openjpeg           pkgs/main/win-64::openjpeg-2.4.0-h4fc8c34_0 
  pillow             pkgs/main/win-64::pillow-10.0.1-py311h045eedc_0 
  ply                pkgs/main/win-64::ply-3.11-py311haa95532_0 
  pyparsing          pkgs/main/win-64::pyparsing-3.0.9-py311haa95532_0 
  pyqt               pkgs/main/win-64::pyqt-5.15.10-py311hd77b12b_0 
  pyqt5-sip          pkgs/main/win-64::pyqt5-sip-12.13.0-py311h2bbff1b_0 
  qt-main            pkgs/main/win-64::qt-main-5.15.2-h19c9488_10 
  sip                pkgs/main/win-64::sip-6.7.12-py311hd77b12b_0 
  tbb                pkgs/main/win-64::tbb-2021.8.0-h59b6b97_0 
  zstd               pkgs/main/win-64::zstd-1.5.5-hd43e919_0 



Downloading and Extracting Packages

icu-73.1             | 29.5 MB   |            |   0% 

pyqt5-sip-12.13.0    | 75 KB     |            |   0% [A


numpy-1.26.3         | 11 KB     |            |   0% [A[A



numpy-base-1.26.3    | 7.3 MB    |            |   0% [A[A[A




matplotlib-3.8.0     | 9 KB      |            |   0% [A[A[A[A





sip-6.7.12           | 615 KB    |            |   0% [A[A[A[A[A






pillow-10.0.1        | 937 KB    |            |   0% [A[A[A[A[A[A







matplotlib-base-3.8. | 7.6 MB    |            |   0% [A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  |            |   0% [A[A[A[A[A[A[A[A









intel-openmp-2023.1. | 2.7 MB    |            |   0% [A[A[A[A[A[A[A[A[A










pyqt-5.15.10         | 4.1 MB    |            |   0% [A[A[A[A[A[A[A[A[A[A











libdeflate-1.17      | 153 KB    |            |   0% [A[A[A[A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   |            |   0% [A[A[A[A[A[A[A[A[A[A[A[A













contourpy-1.2.0      | 218 KB    |            |   0% [A[A[A[A[A[A[A[A[A[A[A[A[A

pyqt5-sip-12.13.0    | 75 KB     | ##1        |  21% [A
icu-73.1             | 29.5 MB   |            |   0% 




matplotlib-3.8.0     | 9 KB      | ########## | 100% [A[A[A[A


numpy-1.26.3         | 11 KB     | ########## | 100% [A[A



numpy-base-1.26.3    | 7.3 MB    |            |   0% [A[A[A





sip-6.7.12           | 615 KB    | 2          |   3% [A[A[A[A[A






pillow-10.0.1        | 937 KB    | 1          |   2% [A[A[A[A[A[A







matplotlib-base-3.8. | 7.6 MB    |            |   0% [A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | 4          |   4% 



numpy-base-1.26.3    | 7.3 MB    | #2         |  13% [A[A[A




matplotlib-3.8.0     | 9 KB      | ########## | 100% [A[A[A[A


numpy-1.26.3         | 11 KB     | ########## | 100% [A[A






pillow-10.0.1        | 937 KB    | #######1   |  72% [A[A[A[A[A[A





sip-6.7.12           | 615 KB    | ########5  |  86% [A[A[A[A[A







matplotlib-base-3.8. | 7.6 MB    | 6          |   7% [A[A[A[A[A[A[A

pyqt5-sip-12.13.0    | 75 KB     | ########## | 100% [A
icu-73.1             | 29.5 MB   | 8          |   9% 

pyqt5-sip-12.13.0    | 75 KB     | ########## | 100% [A



numpy-base-1.26.3    | 7.3 MB    | #9         |  20% [A[A[A








mkl-2023.1.0         | 155.9 MB  |            |   0% [A[A[A[A[A[A[A[A









intel-openmp-2023.1. | 2.7 MB    |            |   1% [A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  |            |   0% [A[A[A[A[A[A[A[A







matplotlib-base-3.8. | 7.6 MB    | #8         |  19% [A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | #2         |  13% 









intel-openmp-2023.1. | 2.7 MB    | #9         |  19% [A[A[A[A[A[A[A[A[A



numpy-base-1.26.3    | 7.3 MB    | ##6        |  27% [A[A[A








mkl-2023.1.0         | 155.9 MB  |            |   1% [A[A[A[A[A[A[A[A







matplotlib-base-3.8. | 7.6 MB    | ##5        |  26% [A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | #5         |  16% 









intel-openmp-2023.1. | 2.7 MB    | ###6       |  37% [A[A[A[A[A[A[A[A[A






pillow-10.0.1        | 937 KB    | ########## | 100% [A[A[A[A[A[A





sip-6.7.12           | 615 KB    | ########## | 100% [A[A[A[A[A
icu-73.1             | 29.5 MB   | #8         |  19% 



numpy-base-1.26.3    | 7.3 MB    | ###5       |  36% [A[A[A








mkl-2023.1.0         | 155.9 MB  |            |   1% [A[A[A[A[A[A[A[A



numpy-base-1.26.3    | 7.3 MB    | ####4      |  44% [A[A[A
icu-73.1             | 29.5 MB   | ##3        |  23% 








mkl-2023.1.0         | 155.9 MB  | 1          |   1% [A[A[A[A[A[A[A[A







matplotlib-base-3.8. | 7.6 MB    | ###2       |  33% [A[A[A[A[A[A[A







matplotlib-base-3.8. | 7.6 MB    | ####9      |  49% [A[A[A[A[A[A[A







matplotlib-base-3.8. | 7.6 MB    | #######3   |  73% [A[A[A[A[A[A[A







matplotlib-base-3.8. | 7.6 MB    | #########8 |  98% [A[A[A[A[A[A[A










pyqt-5.15.10         | 4.1 MB    |            |   0% [A[A[A[A[A[A[A[A[A[A










pyqt-5.15.10         | 4.1 MB    | ##7        |  27% [A[A[A[A[A[A[A[A[A[A










pyqt-5.15.10         | 4.1 MB    | #######6   |  77% [A[A[A[A[A[A[A[A[A[A











libdeflate-1.17      | 153 KB    | #          |  10% [A[A[A[A[A[A[A[A[A[A[A











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libdeflate-1.17      | 153 KB    | ########## | 100% [A[A[A[A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   |            |   0% [A[A[A[A[A[A[A[A[A[A[A[A












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qt-main-5.15.2       | 59.4 MB   | 9          |  10% [A[A[A[A[A[A[A[A[A[A[A[A







matplotlib-base-3.8. | 7.6 MB    | ########## | 100% [A[A[A[A[A[A[A










pyqt-5.15.10         | 4.1 MB    | ########## | 100% [A[A[A[A[A[A[A[A[A[A












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qt-main-5.15.2       | 59.4 MB   | #5         |  16% [A[A[A[A[A[A[A[A[A[A[A[A



numpy-base-1.26.3    | 7.3 MB    | ####9      |  50% [A[A[A












qt-main-5.15.2       | 59.4 MB   | #8         |  19% [A[A[A[A[A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | ##6        |  26% 



numpy-base-1.26.3    | 7.3 MB    | #####4     |  54% [A[A[A












qt-main-5.15.2       | 59.4 MB   | ##         |  20% [A[A[A[A[A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | ##8        |  29% 



numpy-base-1.26.3    | 7.3 MB    | #####7     |  57% [A[A[A












qt-main-5.15.2       | 59.4 MB   | ##1        |  22% [A[A[A[A[A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | ###        |  31% 








mkl-2023.1.0         | 155.9 MB  | 1          |   1% [A[A[A[A[A[A[A[A



numpy-base-1.26.3    | 7.3 MB    | ######6    |  66% [A[A[A












qt-main-5.15.2       | 59.4 MB   | ##3        |  24% [A[A[A[A[A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | ###3       |  34% 



numpy-base-1.26.3    | 7.3 MB    | #######    |  71% [A[A[A












qt-main-5.15.2       | 59.4 MB   | ##4        |  25% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | 1          |   2% [A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | ###5       |  36% 








mkl-2023.1.0         | 155.9 MB  | 1          |   2% [A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | ###7       |  37% 



numpy-base-1.26.3    | 7.3 MB    | #######9   |  80% [A[A[A












qt-main-5.15.2       | 59.4 MB   | ##6        |  26% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | 2          |   2% [A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | ###9       |  40% 



numpy-base-1.26.3    | 7.3 MB    | ########8  |  89% [A[A[A












qt-main-5.15.2       | 59.4 MB   | ##7        |  28% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | 2          |   2% [A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | ####1      |  41% 



numpy-base-1.26.3    | 7.3 MB    | #########3 |  94% [A[A[A












qt-main-5.15.2       | 59.4 MB   | ##8        |  29% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | 2          |   3% [A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | ####4      |  45% 













contourpy-1.2.0      | 218 KB    | 7          |   7% [A[A[A[A[A[A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | ##9        |  29% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | 2          |   3% [A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | ####8      |  49% 













contourpy-1.2.0      | 218 KB    | ########## | 100% [A[A[A[A[A[A[A[A[A[A[A[A[A













contourpy-1.2.0      | 218 KB    | ########## | 100% [A[A[A[A[A[A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | #####2     |  52% 








mkl-2023.1.0         | 155.9 MB  | 3          |   3% [A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | #####5     |  56% 












qt-main-5.15.2       | 59.4 MB   | ###        |  30% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | 3          |   4% [A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | #####8     |  59% 












qt-main-5.15.2       | 59.4 MB   | ###        |  31% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | 4          |   4% [A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | ######1    |  62% 












qt-main-5.15.2       | 59.4 MB   | ###1       |  32% [A[A[A[A[A[A[A[A[A[A[A[A



numpy-base-1.26.3    | 7.3 MB    | ########## | 100% [A[A[A



numpy-base-1.26.3    | 7.3 MB    | ########## | 100% [A[A[A
icu-73.1             | 29.5 MB   | ######4    |  64% 








mkl-2023.1.0         | 155.9 MB  | 4          |   5% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | ###2       |  32% [A[A[A[A[A[A[A[A[A[A[A[A
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mkl-2023.1.0         | 155.9 MB  | 5          |   5% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | ###3       |  33% [A[A[A[A[A[A[A[A[A[A[A[A
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mkl-2023.1.0         | 155.9 MB  | 5          |   6% [A[A[A[A[A[A[A[A












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mkl-2023.1.0         | 155.9 MB  | 5          |   6% [A[A[A[A[A[A[A[A












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mkl-2023.1.0         | 155.9 MB  | 6          |   7% [A[A[A[A[A[A[A[A












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qt-main-5.15.2       | 59.4 MB   | ###9       |  39% [A[A[A[A[A[A[A[A[A[A[A[A
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mkl-2023.1.0         | 155.9 MB  | 7          |   7% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | ####1      |  41% [A[A[A[A[A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | ########6  |  87% 








mkl-2023.1.0         | 155.9 MB  | 7          |   7% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | ####2      |  43% [A[A[A[A[A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | ########8  |  89% 








mkl-2023.1.0         | 155.9 MB  | 7          |   8% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | ####4      |  45% [A[A[A[A[A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | #########1 |  92% 








mkl-2023.1.0         | 155.9 MB  | 7          |   8% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | ####5      |  46% [A[A[A[A[A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | #########4 |  95% 








mkl-2023.1.0         | 155.9 MB  | 8          |   8% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | ####6      |  47% [A[A[A[A[A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | #########6 |  96% 








mkl-2023.1.0         | 155.9 MB  | 8          |   9% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | ####8      |  48% [A[A[A[A[A[A[A[A[A[A[A[A
icu-73.1             | 29.5 MB   | #########9 |  99% 
icu-73.1             | 29.5 MB   | ########## | 100% 












qt-main-5.15.2       | 59.4 MB   | ####9      |  50% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | 8          |   9% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | #####2     |  52% [A[A[A[A[A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | #####3     |  54% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | 9          |   9% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | #####5     |  56% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | 9          |  10% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | #####7     |  57% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | #          |  10% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | #####9     |  59% [A[A[A[A[A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | ######1    |  61% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | #          |  11% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | ######4    |  64% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | #1         |  11% [A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | #1         |  12% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | ######6    |  66% [A[A[A[A[A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | ######8    |  68% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | #2         |  12% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | #######    |  71% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | #2         |  13% [A[A[A[A[A[A[A[A









intel-openmp-2023.1. | 2.7 MB    | #####      |  50% [A[A[A[A[A[A[A[A[A









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mkl-2023.1.0         | 155.9 MB  | #3         |  13% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | #######2   |  72% [A[A[A[A[A[A[A[A[A[A[A[A









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mkl-2023.1.0         | 155.9 MB  | #3         |  14% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | #######3   |  73% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | #4         |  14% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | #######5   |  76% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | #4         |  15% [A[A[A[A[A[A[A[A









intel-openmp-2023.1. | 2.7 MB    | ######6    |  66% [A[A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | #######7   |  78% [A[A[A[A[A[A[A[A[A[A[A[A









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mkl-2023.1.0         | 155.9 MB  | #5         |  15% [A[A[A[A[A[A[A[A












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mkl-2023.1.0         | 155.9 MB  | #5         |  16% [A[A[A[A[A[A[A[A









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intel-openmp-2023.1. | 2.7 MB    | ########## | 100% [A[A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | ########   |  81% [A[A[A[A[A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | ########3  |  83% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | #5         |  16% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | ########6  |  86% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | #6         |  17% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | ########8  |  89% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | #7         |  17% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | #########1 |  91% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | #7         |  17% [A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | #8         |  18% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | #########3 |  93% [A[A[A[A[A[A[A[A[A[A[A[A








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mkl-2023.1.0         | 155.9 MB  | ##         |  20% [A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | ##1        |  21% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | #########4 |  94% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | ##2        |  22% [A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | ##2        |  23% [A[A[A[A[A[A[A[A












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mkl-2023.1.0         | 155.9 MB  | ##4        |  25% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | #########6 |  96% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | ##5        |  25% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | #########7 |  97% [A[A[A[A[A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | ##6        |  26% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | #########8 |  98% [A[A[A[A[A[A[A[A[A[A[A[A








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mkl-2023.1.0         | 155.9 MB  | ####6      |  47% [A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | ####8      |  49% [A[A[A[A[A[A[A[A








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mkl-2023.1.0         | 155.9 MB  | #####1     |  52% [A[A[A[A[A[A[A[A








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mkl-2023.1.0         | 155.9 MB  | #####9     |  60% [A[A[A[A[A[A[A[A












qt-main-5.15.2       | 59.4 MB   | ########## | 100% [A[A[A[A[A[A[A[A[A[A[A[A












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mkl-2023.1.0         | 155.9 MB  | ######     |  61% [A[A[A[A[A[A[A[A








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mkl-2023.1.0         | 155.9 MB  | #######2   |  72% [A[A[A[A[A[A[A[A








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mkl-2023.1.0         | 155.9 MB  | ########   |  80% [A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | ########2  |  82% [A[A[A[A[A[A[A[A








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mkl-2023.1.0         | 155.9 MB  | #########  |  90% [A[A[A[A[A[A[A[A








mkl-2023.1.0         | 155.9 MB  | #########1 |  91% [A[A[A[A[A[A[A[A








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mkl-2023.1.0         | 155.9 MB  | #########3 |  94% [A[A[A[A[A[A[A[A








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mkl-2023.1.0         | 155.9 MB  | #########8 |  99% [A[A[A[A[A[A[A[A








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mkl-2023.1.0         | 155.9 MB  | ########## | 100% [A[A[A[A[A[A[A[A
                                                     


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Preparing transaction: ...working... done
Verifying transaction: ...working... done
Executing transaction: ...working... done

Note: you may need to restart the kernel to use updated packages.


==> WARNING: A newer version of conda exists. <==
  current version: 23.7.4
  latest version: 23.11.0

Please update conda by running

    $ conda update -n base -c defaults conda

Or to minimize the number of packages updated during conda update use

     conda install conda=23.11.0

In [2]:

conda install scikit-learn

Collecting package metadata (current_repodata.json): ...working... done
Note: you may need to restart the kernel to use updated packages.


==> WARNING: A newer version of conda exists. <==
  current version: 23.7.4
  latest version: 23.11.0

Please update conda by running

    $ conda update -n base -c defaults conda

Or to minimize the number of packages updated during conda update use

     conda install conda=23.11.0

Solving environment: ...working... done

## Package Plan ##

  environment location: C:\Users\369rental\anaconda3\envs\jupyter

  added / updated specs:
    - scikit-learn


The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    scikit-learn-1.2.2         |  py311hd77b12b_1         7.6 MB
    scipy-1.11.4               |  py311hc1ccb85_0        20.9 MB
    ------------------------------------------------------------
                                           Total:        28.5 MB

The following NEW packages will be INSTALLED:

  icc_rt             pkgs/main/win-64::icc_rt-2022.1.0-h6049295_2 
  joblib             pkgs/main/win-64::joblib-1.2.0-py311haa95532_0 
  scikit-learn       pkgs/main/win-64::scikit-learn-1.2.2-py311hd77b12b_1 
  scipy              pkgs/main/win-64::scipy-1.11.4-py311hc1ccb85_0 
  threadpoolctl      pkgs/main/noarch::threadpoolctl-2.2.0-pyh0d69192_0 



Downloading and Extracting Packages

scikit-learn-1.2.2   | 7.6 MB    |            |   0% 

scipy-1.11.4         | 20.9 MB   |            |   0% [A
scikit-learn-1.2.2   | 7.6 MB    |            |   0% 

scipy-1.11.4         | 20.9 MB   |            |   0% [A
scikit-learn-1.2.2   | 7.6 MB    | ####       |  40% 

scipy-1.11.4         | 20.9 MB   | 2          |   2% [A
scikit-learn-1.2.2   | 7.6 MB    | #######3   |  73% 

scipy-1.11.4         | 20.9 MB   | 4          |   5% [A

scipy-1.11.4         | 20.9 MB   | 7          |   8% [A

scipy-1.11.4         | 20.9 MB   | #1         |  12% [A

scipy-1.11.4         | 20.9 MB   | ##2        |  22% [A

scipy-1.11.4         | 20.9 MB   | ###3       |  34% [A

scipy-1.11.4         | 20.9 MB   | ####5      |  46% [A
scikit-learn-1.2.2   | 7.6 MB    | ########## | 100% 

scipy-1.11.4         | 20.9 MB   | #####2     |  52% [A

scipy-1.11.4         | 20.9 MB   | ######3    |  64% [A

scipy-1.11.4         | 20.9 MB   | #######2   |  72% [A

scipy-1.11.4         | 20.9 MB   | #######8   |  79% [A

scipy-1.11.4         | 20.9 MB   | #########3 |  93% [A

scipy-1.11.4         | 20.9 MB   | ########## | 100% [A
                                                     


                                                     [A

Preparing transaction: ...working... done
Verifying transaction: ...working... done
Executing transaction: ...working... 

    Windows 64-bit packages of scikit-learn can be accelerated using scikit-learn-intelex.
    More details are available here: https://intel.github.io/scikit-learn-intelex

    For example:

        $ conda install scikit-learn-intelex
        $ python -m sklearnex my_application.py


done

In [3]:

conda install pandas

Collecting package metadata (current_repodata.json): ...working... done
Note: you may need to restart the kernel to use updated packages.

Solving environment: ...working... done

## Package Plan ##

  environment location: C:\Users\369rental\anaconda3\envs\jupyter

  added / updated specs:
    - pandas


The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    numexpr-2.8.7              |  py311h1fcbade_0         160 KB
    pandas-2.1.4               |  py311hf62ec03_0        13.6 MB
    ------------------------------------------------------------
                                           Total:        13.7 MB

The following NEW packages will be INSTALLED:

  bottleneck         pkgs/main/win-64::bottleneck-1.3.5-py311h5bb9823_0 
  numexpr            pkgs/main/win-64::numexpr-2.8.7-py311h1fcbade_0 
  pandas             pkgs/main/win-64::pandas-2.1.4-py311hf62ec03_0 
  python-tzdata      pkgs/main/noarch::python-tzdata-2023.3-pyhd3eb1b0_0 



Downloading and Extracting Packages

numexpr-2.8.7        | 160 KB    |            |   0% 

pandas-2.1.4         | 13.6 MB   |            |   0% [A

pandas-2.1.4         | 13.6 MB   |            |   0% [A
numexpr-2.8.7        | 160 KB    | #          |  10% 

pandas-2.1.4         | 13.6 MB   | ##         |  20% [A
numexpr-2.8.7        | 160 KB    | ########## | 100% 
numexpr-2.8.7        | 160 KB    | ########## | 100% 

pandas-2.1.4         | 13.6 MB   | ###3       |  34% [A

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Preparing transaction: ...working... done
Verifying transaction: ...working... done
Executing transaction: ...working... done


==> WARNING: A newer version of conda exists. <==
  current version: 23.7.4
  latest version: 23.11.0

Please update conda by running

    $ conda update -n base -c defaults conda

Or to minimize the number of packages updated during conda update use

     conda install conda=23.11.0

In [4]:

conda install openpyxl

Collecting package metadata (current_repodata.json): ...working... done
Note: you may need to restart the kernel to use updated packages.

Solving environment: ...working... done

## Package Plan ##

  environment location: C:\Users\369rental\anaconda3\envs\jupyter

  added / updated specs:
    - openpyxl


The following NEW packages will be INSTALLED:

  et_xmlfile         pkgs/main/win-64::et_xmlfile-1.1.0-py311haa95532_0 
  openpyxl           pkgs/main/win-64::openpyxl-3.0.10-py311h2bbff1b_0 



Downloading and Extracting Packages


Preparing transaction: ...working... done
Verifying transaction: ...working... done
Executing transaction: ...working... done


==> WARNING: A newer version of conda exists. <==
  current version: 23.7.4
  latest version: 23.11.0

Please update conda by running

    $ conda update -n base -c defaults conda

Or to minimize the number of packages updated during conda update use

     conda install conda=23.11.0

In [ ]:

80 KiB Raw Permalink Blame History

80 KiB

Raw Permalink Blame History