python - 合并具有不同索引的 3 个数据帧

Question

我有 3 个 DF:GDP、能源、ScimEn。

print(GDP.index.name) > Country
print(energy.index.name) > None
print(ScimEn.index.name) > None

尽管 energy 和 ScimEn 确实有一个“国家/地区”列。 我想合并“国家”上的所有 DF。我怎样才能做到这一点？我已尝试执行以下操作

newdf = (pd.merge(energy, ScimEn, how='inner', on='Country').merge(GDP, how='inner', on=GDP.index.name))
> KeyError: 'Country'

如果我尝试:

newdf = (pd.merge(energy, ScimEn, how='inner', on='Country').
         merge(GDP, how='inner', left_index=True))
    raise MergeError('Must pass right_on or right_index=True')
pandas.tools.merge.MergeError: Must pass right_on or right_index=True

如果我尝试:

newdf = (pd.merge(energy, ScimEn, how='inner', on='Country').
         merge(GDP, how='inner', left_index=True, right_index=True))

它返回:

Empty DataFrame
Columns: [Country, Energy Supply, Energy Supply per Capita, % Renewable, Rank, Documents, Citable documents, Citations, Self-citations, Citations per document, H index, Country Code, Indicator Name, Indicator Code, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015]
Index: []

Answer 1

您可以添加 reset_index GDP:

newdf = pd.merge(energy.reset_index(), ScimEn, on='Country').merge(GDP.reset_index(), on='Country')

如果有很多 DataFrames 则可以选择:

from  functools import reduce
dfs = [energy.reset_index(), ScimEn, GDP.reset_index()]
newdf = reduce(lambda left,right: pd.merge(left,right,on='Country'), dfs)

没有 reset_index 的解决方案 join :

newdf = pd.merge(energy.reset_index(), ScimEn, on='Country').join(GDP, on='Country', how='inner')