Created
January 29, 2018 11:51
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Guarda datos de un DataFrame en formato CSV en Python.
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| import pandas as pd | |
| # Definición diccionario: | |
| diccionario = {'pares': [0, 2, 4, 6], 'impares': [1, 3, 5, 7]} | |
| # Creación DataFrame: | |
| df_numeros = pd.DataFrame(diccionario) | |
| # Guarda datos en CSV: | |
| df_numeros.to_csv('numeros.csv', header=False, index=False) |
estoy aprendiendo python con jupiter notebook y me da este mensage c:\Users\oscar\AppData\Local\Programs\Python\Python311\Lib\site-packages\sklearn\linear_model_logistic.py:458: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.
Increase the number of iterations (max_iter) or scale the data as shown in:
https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
n_iter_i = _check_optimize_result(
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estoy aprendiendo python con jupiter notebook y me da este mensage c:\Users\oscar\AppData\Local\Programs\Python\Python311\Lib\site-packages\sklearn\linear_model_logistic.py:458: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.
Increase the number of iterations (max_iter) or scale the data as shown in:
https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
n_iter_i = _check_optimize_result(