I have two dfs
xx
AVERAGE_CALL_DURATION | AVERAGE_DURATION | CHANGE_OF_DETAILS |
---|---|---|
267 | 298 0 | 0 |
421 | 609.33 | 0.33 |
330 | 334 0 | 0 |
240.5 | 666.5 | 0 |
628 | 713 0 | 0 |
and
NoC_c
AVERAGE_CALL_DURATION | AVERAGE_DURATION | CHANGE_OF_DETAILS |
---|---|---|
-5.93 | -4.95 | 0.90 |
593.50 | 595.70 | 1.00 |
I want to return 1 if the xx
column contains the range within NoC_c
(where column names are the same
I can do this for one column
def check_between_ranges(xx, NoC_c):
ranges = NoC_c['AVERAGE_CALL_DURATION']
if (xx['AVERAGE_CALL_DURATION'] >= ranges.iloc[0]) and (xx['AVERAGE_CALL_DURATION'] <= ranges.iloc[1]):
return 1
return xx['AVERAGE_CALL_DURATION']
xx['AVERAGE_CALL_DURATION2'] = xx.apply(lambda x: check_between_ranges(x, NoC_c), axis=1)
However, I need remove the element of manually specifying the column name as the actual dfs contain many more columns.
I have tried
a = NoC_c.columns
def check_between_ranges(xx, NoC_c):
ranges = NoC_c[a]
if (xx[a] >= ranges.iloc[0]) & (xx[a] <= ranges.iloc[1]):
return 1
xx.apply(lambda x: check_between_ranges(x, NoC_c[a]), axis=1)
However, I get the error
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()
.
I tried the solutions listed here, although, they were unsuccessful
Also read this to address the specific error but didn't aid in my issue
Any help would be appreciated.
Traceback (most recent call last):
File "<ipython-input-11-2affca771555>", line 10, in <module>
xx.apply(lambda x: check_between_ranges(x, NoC_c[a]), axis=1)
File "C:\Program Files\Anaconda3\lib\site-packages\pandas\core\frame.py", line 7552, in apply
return op.get_result()
File "C:\Program Files\Anaconda3\lib\site-packages\pandas\core\apply.py", line 185, in get_result
return self.apply_standard()
File "C:\Program Files\Anaconda3\lib\site-packages\pandas\core\apply.py", line 276, in apply_standard
results, res_index = self.apply_series_generator()
File "C:\Program Files\Anaconda3\lib\site-packages\pandas\core\apply.py", line 305, in apply_series_generator
results[i] = self.f(v)
File "<ipython-input-11-2affca771555>", line 10, in <lambda>
xx.apply(lambda x: check_between_ranges(x, NoC_c[a]), axis=1)
File "<ipython-input-11-2affca771555>", line 6, in check_between_ranges
if (xx[a] >= ranges.iloc[0]) & (xx[a] <= ranges.iloc[1]):
File "C:\Program Files\Anaconda3\lib\site-packages\pandas\core\generic.py", line 1330, in __nonzero__
f"The truth value of a {type(self).__name__} is ambiguous. "
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
CodePudding user response:
You have almost the solution. Try to add .all()
, docs here:
def check_between_ranges(xx, NoC_c):
ranges = NoC_c[a]
if (xx[a] >= ranges.iloc[0]).all() & (xx[a] <= ranges.iloc[1]).all():
return 1
CodePudding user response:
Would this work for you?
Comparison Function
def check_between_ranges(x):
v = []
for c in x.index:
if (x[c] >= NoC_c.at[0,c]) & (x[c] <= NoC_c.at[1,c]):
v = [1]
else:
v = [x[c]]
return pd.Series(v, index=x.index)
Execution
xx.apply(check_between_ranges, axis=1)
Result
AVERAGE_CALL_DURATION AVERAGE_DURATION CHANGE_OF_DETAILS
0 1.0 1.00 0.00
1 1.0 609.33 0.33
2 1.0 1.00 0.00
3 1.0 666.50 0.00
4 628.0 713.00 0.00