Pandas：根据 2 个系列之间的差异创建列表

Question

I am writing a custom error message when 2 Pandas series are not equal and want to use '<' to point at the differences.

Here's the workflow for a failed equality:

1. Convert both lists to Python: pd.Series([list])
2. Side by side comparison in a dataframe: table = pd.concat([list1], [list2]), axis=1
3. Add column and index names: table.columns = ['...', '...'] , table.index = ['...', '...']

Current output:

|Yours|Actual|

|1|1|

|2|2|

|4|3|

Desired output:

|Yours|Actual|-|

|1|1||

|2|2||

|4|3|<|

The naive solution is iterating through each list index and if it's not equal, appending '<' to another list then putting this list into pd.concat() but I am looking for a method using Pandas. For example,

error_series = '<' if (abs(yours - actual) >= 1).all(axis=None) else ''

Ideally it would append '<' to a list if the difference between the results is greater than the Margin of Error of 1, otherwise append nothing

Note: Removed tables due to StackOverflow being picky and not letting my post my question

Answer 1

You can create the DF and give index and column names in one line:

import pandas as pd
list1 = [1,2,4]
list2 = [1,2,10]
df = pd.DataFrame(zip(list1, list2), columns=['Yours', 'Actual'])

Create a boolean mask to find the rows that have a too large difference:

margin_of_error = 1
mask = df.diff(axis=1)['Actual'].abs()>margin_of_error

Add a column to the DF and set the values of the mask as you want:

df['too_different'] = df.diff(axis=1)['Actual'].abs()>margin_of_error
df['too_different'].replace(True, '<', inplace=True)
df['too_different'].replace(False, '', inplace=True)

output:

   Yours  Actual too_different
0      1       1              
1      2       2              
2      4      10             <

Answer 2

or you can do something like this:

df = df.assign(diffr=df.apply(lambda x: '<' 
                              if (abs(x['yours'] - x['actual']) >= 1) 
                              else '', axis=1))
print(df)
'''
   yours  actual diffr
0      1       1      
1      2       2      
2      4       3     <