小编Iva*_*van的帖子

我用

"""Data taken from https://datos.gob.mx/busca/organization/conapo and 
https://es.wikipedia.org/wiki/Anexo:Entidades_federativas_de_M%C3%A9xico_por_superficie,_poblaci%C3%B3n_y_densidad """

total_population_segmentation = pd.read_html('professional_segmentation_mexico.html')
population_segmentation = pd.read_html('population_segmentation.html')

其次是

total_population_segmentation = population_segmentation[2]
total_population_segmentation = total_population_segmentation['Población histórica de México']
total_population_segmentation = total_population_segmentation.drop('Pos',axis=1)
total_population_segmentation = total_population_segmentation.sort_values('Entidad').reset_index().drop('index',axis=1)

因此，我正在使用以下 DataFrame

    total_population_segmentation.head(5)

我用过total_population_segmentation.dtypes，我得到了

Entidad    object
2010       object
2015       object
2020       object
2025       object
2030       object
dtype: object

我曾经pd.to_numeric(total_population_segmentation['2010'])检查它是否有效，但我得到了

ValueError                                Traceback (most recent call last)
pandas\_libs\lib.pyx in pandas._libs.lib.maybe_convert_numeric()

ValueError: Unable to parse string "1 195 787"

During handling of the above exception, another exception occurred:

ValueError …