我有兩個(gè)CSV文件，我正在比較并僅并排返回具有不同值的列。df1Country 1980    1981    1982    1983    1984Bermuda 0.00793 0.00687 0.00727 0.00971 0.00752Canada  9.6947  9.58952 9.20637 9.18989 9.78546Greenland   0.00791 0.00746 0.00722 0.00505 0.00799Mexico  3.72819 4.11969 4.33477 4.06414 4.18464df2Country 1980    1981    1982    1983    1984Bermuda 0.77777 0.00687 0.00727 0.00971 0.00752Canada  9.6947  9.58952 9.20637 9.18989 9.78546Greenland   0.00791 0.00746 0.00722 0.00505 0.00799Mexico  3.72819 4.11969 4.33477 4.06414 4.18464import pandas as pdimport numpy as npdf1=pd.read_csv('csv1.csv')df2=pd.read_csv('csv2.csv')def diff_pd(df1, df2):    """Identify differences between two pandas DataFrames"""    assert (df1.columns == df2.columns).all(), \        "DataFrame column names are different"    if any(df1.dtypes != df2.dtypes):        "Data Types are different, trying to convert"        df2 = df2.astype(df1.dtypes)    if df1.equals(df2):        print("Dataframes are the same")        return None    else:        # need to account for np.nan != np.nan returning True        diff_mask = (df1 != df2) & ~(df1.isnull() & df2.isnull())        ne_stacked = diff_mask.stack()        changed = ne_stacked[ne_stacked]        changed.index.names = ['Country', 'Column']        difference_locations = np.where(diff_mask)        changed_from = df1.values[difference_locations][0]        changed_to = df2.values[difference_locations]        y=pd.DataFrame({'From': changed_from, 'To': changed_to},                            index=changed.index)        print(y)        return pd.DataFrame({'From': changed_from, 'To': changed_to},                            index=changed.index)diff_pd(df1,df2)我當(dāng)前的輸出是：                   From       ToCountry Column                  0       1980    0.00793  0.77777因此，我想獲得索引值不匹配的行的國(guó)家/地區(qū)名稱，而不是索引0。下面是一個(gè)例子。我希望我的輸出是：                   From       ToCountry Column                  Bermuda  1980    0.00793  0.77777謝謝所有能提供解決方案的人。