Question

我正在处理两个非常相似的数据帧，我试图弄清楚如何获取一个而不是另一个的数据 - 反之亦然。

到目前为止，这是我的代码：

import pandas as pd
import numpy as np


def report_diff(x):
return x[0] if x[0] == x[1] else '{} ---> {}'.format(*x)

old = pd.read_excel('File 1')
new = pd.read_excel('File 2')
old['version'] = 'old'
new['version'] = 'new'

full_set = pd.concat([old,new],ignore_index=True)

changes = full_set.drop_duplicates(subset=['ID','Type', 'Total'], keep='last')

duplicated = changes.duplicated(subset=['ID', 'Type'], keep=False)

dupe_accts = changes[duplicated]

change_new = dupe_accts[(dupe_accts['version'] == 'new')]

change_old = dupe_accts[(dupe_accts['version'] == 'old' )]

change_new = change_new.drop(['version'], axis=1)

change_old = change_old.drop(['version'],axis=1)

change_new.set_index('Employee ID', inplace=True)

change_old.set_index('Employee ID', inplace=True)

diff_panel = pd.Panel(dict(df1=change_old,df2=change_new))
diff_output = diff_panel.apply(report_diff, axis=0)

所以下一步就是获取仅旧的数据，而且只有新数据。

我的第一次尝试是：

 changes['duplicate']=changes['Employee ID'].isin(dupe_accts)
removed_accounts = changes[(changes['duplicate'] == False) & (changes['version'] =='old')]

Answer 1

我头晕目眩地看着你的代码！

IIUC：

在indicator=True

中使用参数merge

考虑数据框old和new

old = pd.DataFrame(dict(
        ID=[1, 2, 3, 4, 5],
        Type=list('AAABB'),
        Total=[9 for _ in range(5)],
        ArbitraryColumn=['blah' for _ in range(5)]
    ))

new = old.head(2)

然后merge和query left_only

old.merge(
    new, 'outer', on=['ID', 'Type'],
    suffixes=['', '_'], indicator=True
).query('_merge == "left_only"')

  ArbitraryColumn  ID  Total Type ArbitraryColumn_  Total_     _merge
2            blah   3      9    A              NaN     NaN  left_only
3            blah   4      9    B              NaN     NaN  left_only
4            blah   5      9    B              NaN     NaN  left_only

我们可以reindex限制原始列

old.merge(
    new, 'outer', on=['ID', 'Type'],
    suffixes=['', '_'], indicator=True
).query('_merge == "left_only"').reindex_axis(old.columns, axis=1)

  ArbitraryColumn  ID  Total Type
2            blah   3      9    A
3            blah   4      9    B
4            blah   5      9    B

Python如何获取一个数据帧但不是一秒的值

1 个答案: