Python pandas：高效地比较数据帧的行？

Question

我有数据框 'dfm' :

match             group  
adamant           86   
adamant           86   
adamant bild      86   
360works          94   
360works          94

其中'group'列相同，我想将'match'列的内容两两比较，并将比较结果添加到另一列'result'中。例如预期结果将是：

   group        compare                              result
    86      adamant, adamant                          same
    86      adamant, adamant bild                   not same
    86      adamant, adamant bild                   not same 
    94      360works,360works                         same

有人可以帮忙吗？

Answer 1

有点hacky，但它似乎对我有用：

# initialize the list to store the dictionaries
# that will create the new DataFrame
new_df_dicts = []

# group on 'group'
for group, indices in dfm.groupby('group').groups.iteritems():
    # get the values in the 'match' column
    vals = dfm.ix[indices]['match'].values
    # choose every possible pair from the array of column values
    for i in range(len(vals)):
        for j in range(i+1, len(vals)):
            # compute the new values
            compare = vals[i] + ', ' + vals[j]
            if vals[i] == vals[j]:
                result = 'same'
            else:
                result = 'not same'
            # append the results to the DataFrame
            new_df_dicts.append({'group': group, 'compare': compare, 'result': result})

# create the new DataFrame
new_df = DataFrame(new_df_dicts)

这是我的输出：

                 compare  group    result
0     360works, 360works     94      same
1       adamant, adamant     86      same
2  adamant, adamant bild     86  not same
3  adamant, adamant bild     86  not same

之前我建议将行附加到已初始化的 DataFrame。从字典列表创建一个 DataFrame，而不是对 DataFrame 进行多次追加，运行速度大约快 9-10 倍。

Answer 2

这是另一种选择。虽然不确定它是否更有效率

import itertools
import pandas as pd

new_df = pd.DataFrame()
for grp in set( dfm['group']):
    for combo in itertools.combinations( dfm[dfm['group'] == grp].index, 2 ):
        # compute the new values
        match1 = dfm['match'][combo[0]]
        match2 = dfm['match'][combo[0]]
        compare = match1 + ', ' + match2
        if match1 == match2:
            result = 'same'
        else:
            result = 'not same'
        # append the results to the DataFrame
        new_df = new_df.append({'group': grp, 'compare': compare, 'result': result}, ignore_index=True)

print new_df

（格式借鉴自 James 的回答）

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