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Verifico que anda todo con Poetry
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notebooks/clase_01_introduccion.ipynb

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notebooks/clase_02_visualizacion.ipynb

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notebooks/clase_03_1_outliers.ipynb

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notebooks/clase_03_2_codificacion.ipynb

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notebooks/clase_03_3_discretizacion.ipynb

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notebooks/clase_03_4_desbalance.ipynb

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notebooks/clase_03_5_normalizacion_estandarizacion.ipynb

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notebooks/clase_03_datos_faltantes.ipynb

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notebooks/clase_03_variables_categoricas.ipynb

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notebooks/clase_04_tests_inferenciales.ipynb

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notebooks/clase_05_reduccion_de_dimensionalidad.ipynb

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notebooks/clase_06_taller-pca.ipynb

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notebooks/clase_06_taller-visualizaciones.ipynb

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notebooks/clase_06_taller.ipynb

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notebooks/clase_08_EDA_audio.ipynb

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notebooks/clase_08_EDA_imagenes.ipynb

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notebooks/clase_08_EDA_texto.ipynb

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notebooks/clase_08_PCA_imagenes.ipynb

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notebooks/clase_08_eda_automatico.ipynb

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poetry.lock

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pyproject.toml

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@@ -8,17 +8,32 @@ requires-python = ">=3.11,<3.13"
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dependencies = [
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"requests (>=2.32.3,<3.0.0)",
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"sqlalchemy (>=2.0.38,<3.0.0)",
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"pandas (>=2.2.3,<3.0.0)",
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#"pandas (>=2.2.3,<3.0.0)",
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"pandas (>=2.1.4,<2.2.0)",
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"ydata-profiling (>=4.12.2,<5.0.0)",
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"matplotlib (>=3.10.1,<4.0.0)",
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"matplotlib (>=3.7.0,<4.0.0)",
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#"matplotlib (>=3.10.1,<4.0.0)",
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"seaborn (>=0.13.2,<0.14.0)",
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"scipy (>=1.15.2,<2.0.0)",
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"scikit-learn (>=1.6.1,<2.0.0)",
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#"scipy (>=1.15.2,<2.0.0)",
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"scipy (>=1.6.1,<=1.11.4)",
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"numpy (>1.26.3 ,<=1.26.4)",
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#"scikit-learn (>=1.6.1,<2.0.0)",
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"scikit-learn (>=0.24,<1.5.0)",
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"ipykernel (>=6.29.5,<7.0.0)",
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"beautifulsoup4 (>=4.13.3,<5.0.0)",
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"jupyter (>=1.1.1,<2.0.0)",
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"h11 (>=0.16.0)",
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"Jinja2 (>=3.1.6)",
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"missingno (>=0.5.2,<0.6.0)",
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"imblearn (>=0.0,<0.1)",
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"librosa (>=0.11.0,<0.12.0)",
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"sweetviz (>=2.3.1,<3.0.0)",
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"category-encoders (>=2.6.0,<3.0.0)",
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"kaleido (==0.2.1)",
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"pycaret (>=3.3.2,<4.0.0)",
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"tensorflow (>=2.19.0,<3.0.0)",
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"nltk (>=3.9.1,<4.0.0)",
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"rasterio (>=1.4.3,<2.0.0)",
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]
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recursos/sweetviz_comparacion.html

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recursos/sweetviz_fix.md

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Para solucionar este problema, se recomienda seguir uno de los siguientes pasos:
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1. Hacer un downgrade de Numpy a la versión 1.26.4
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En conda:
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```bash
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conda install numpy=1.26.4
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```
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Localizar el archivo graph_numeric.py (está localizado dentro de la carpeta de instalación de Sweetviz) y realizar los siguientes cambios:
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2. Localizar el archivo graph_numeric.py (está localizado dentro de la carpeta de instalación de Sweetviz) y realizar los siguientes cambios:
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1. Importar la siguiente librería al inicio del archivo:
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```python
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from numpy.exceptions import VisibleDeprecationWarning
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```
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En las líneas 71 y 74, cambiar
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2. En las líneas 71 y 74, cambiar
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```python
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category = VisibleDeprecationWarning
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category=np.exceptions.VisibleDeprecationWarning
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```
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Reiniciar el kernel de Jupyter y ejecutar.
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3. Reiniciar el kernel de Jupyter y ejecutar.
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Nota: el archivo graph_numeric.py se encuentra en las siguiente rutas:
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1) ...miniconda3/envs/add-env/lib/sweetviz/graph_numeric.py
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2) ...pypoetry/virtualenvs/ceia-analisis-de-datos-xxxxxx-<version>/lib/python3.11/site-packages/sweetviz/graph_numeric.py

recursos/sweetviz_report.html

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recursos/titanic_report_1.html

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