比较两个熊猫数据框的差异

Question

I have two dataframes and I want to compare them, then display the differences side by side. I had been using the accepted solution from this question , but am now getting an error with ne_stacked = (current_df != new_df).stack() .

This used to work fine, but the error I'm getting now is The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all(). The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all(). . After looking at the documentation for all of these options I'm not sure how to implement any of them and keep the same functionality in my code.

How would I go about replacing ne_stacked = (current_df != new_df).stack() so I don't get the ambiguity error?

EDIT

Basic code example as requested:

d = {'a':[1,2,3],'b':[1,2,3],'c':[1,2,3]}
d2 = {'a':[4,2,3],'b':[1,4,3],'c':[1,2,4]}
df1 = pd.DataFrame(d)
df2 = pd.DataFrame(d2)
print (df1 != df2) //returns true when value in df1 is not equal to df2

       a      b      c
0   True  False  False
1  False   True  False
2  False  False   True

So the != expression works just fine for this simple dataframe, but not the more complex ones I'm using (below).

df1 = {'CORE': [{'satellite': '2B',
   'windowEnd': '2015-218 04:00:00',
   'windowStart': '2015-217 20:00:00'}],
 'DURATION': [500.0],
 'PRIORITY': [5],
 'RATE': [u'HIGH_RATE'],
 'STATUS': [u'ACTIVE'],
 'TASK_ID': [1],
 'TYPE': [u'NOMINAL'],
 'WINDOW_END': ['2015-218 04:00:00'],
 'WINDOW_START': ['2015-217 20:00:00']}

df2 = {'CORE': [{'satellite': '2B',
   'windowEnd': '2015-220 04:00:00',
   'windowStart': '2015-219 20:00:00'}],
 'DURATION': [500.0],
 'PRIORITY': [5],
 'RATE': [u'HIGH_RATE'],
 'STATUS': [u'ACTIVE'],
 'TASK_ID': [2],
 'TYPE': [u'NOMINAL'],
 'WINDOW_END': ['2015-220 04:00:00'],
 'WINDOW_START': ['2015-219 20:00:00']}

Answer 1

I'm using pandas version '0.16.2' and I couldn't see any error when I tried to evaluate df1 != df2 .

Take a look at my code below:

import pandas as pd

d1 = {'CORE': [{'satellite': '2B',
  'windowEnd': '2015-218 04:00:00',
  'windowStart': '2015-217 20:00:00'}],
  'DURATION': [500.0],
  'PRIORITY': [5],
  'RATE': [u'HIGH_RATE'],
  'STATUS': [u'ACTIVE'],
  'TASK_ID': [1],
  'TYPE': [u'NOMINAL'],
  'WINDOW_END': ['2015-218 04:00:00'],
  'WINDOW_START': ['2015-217 20:00:00']}

d2 = {'CORE': [{'satellite': '2B',
  'windowEnd': '2015-220 04:00:00',
  'windowStart': '2015-219 20:00:00'}],
  'DURATION': [500.0],
  'PRIORITY': [5],
  'RATE': [u'HIGH_RATE'],
  'STATUS': [u'ACTIVE'],
  'TASK_ID': [2],
  'TYPE': [u'NOMINAL'],
  'WINDOW_END': ['2015-220 04:00:00'],
  'WINDOW_START': ['2015-219 20:00:00']}

df1 = pd.DataFrame(d1)
df2 = pd.DataFrame(d2)
print (df1 != df2)

# It was printed:
#    CORE   DURATION  PRIORITY   RATE   STATUS  TASK_ID  TYPE    WINDOW_END WINDOW_START
# 0  True   False     False      False  False   True     False   True       True

You could also try to use .any() :

print (df1 != df2).any(axis=0)
# It was printed:
# CORE             True
# DURATION        False
# PRIORITY        False
# RATE            False
# STATUS          False
# TASK_ID          True
# TYPE            False
# WINDOW_END       True
# WINDOW_START     True
# dtype: bool

Take care with .any() , because it will look for any True values in the entire row/column. I don't know if you need that.