我试图获取世界银行的一系列健康指标数据。在
使用以下代码访问世界银行数据:
进口:
import wbdata
import datetime
查看不同的指标:
^{pr2}$这将返回以下结果:
SP.DYN.TFRT.IN Fertility rate, total (births per woman)
SP.DYN.SMAM.MA Mean age at first marriage, male
SP.DYN.SMAM.FE Mean age at first marriage, female
要访问特定国家或地区的数据,请使用以下代码:
data_dates = (datetime.datetime(2015,1,1), datetime.datetime(2015,1,1))
top_20_data = wbdata.get_dataframe({'SP.DYN.TFRT.IN':'Fertility rate, total (births per woman)','SP.DYN.SMAM.MA':'Mean age at first marriage, male'},
country=('BE','BG','CZ','DK','DE','EE','IE','GR','ES','FR','HR','IT','CY','LV','LT','LU',
'HU','MT','NL','AT','PL','PT','RO','SI','SK','FI','SE','GBR'),
data_date=data_dates,
convert_date=False, keep_levels=True)
我要做的是把每一个指标输入数据框和每一个描述。在
我尝试创建一个小样本pandas数据框架:
data = {'Indicator': ['SP.DYN.TFRT.IN', 'SP.DYN.SMAM.MA', 'SP.DYN.SMAM.MA'],
'Description': ['Fertility rate, total (births per woman)', 'Mean age at first marriage, male', 'Mean age at first marriage, female']}
df = pd.DataFrame(data, columns=['Indicator', 'Description'])
把这个传给wdata.get_daframe像这样:
top_20_data = wbdata.get_dataframe({df['Indicator']:df['Description']},
country=('BE','BG','CZ','DK','DE','EE','IE','GR','ES','FR','HR','IT','CY','LV','LT','LU',
'HU','MT','NL','AT','PL','PT','RO','SI','SK','FI','SE','GBR'),
data_date=data_dates,
convert_date=False, keep_levels=True)
但我收到以下错误:
TypeError: 'Series' objects are mutable, thus they cannot be hashed
我在网上查了一下,但没有发现什么特别有用的东西。在
将
DataFrame
转换为字典:相关问题 更多 >
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