Error when trying to apply lambda function using pandas Dataframe

Question

I have a dataframe with a datetime index, which looks like this:

                         ModelRun  Tmp_2m_C     DSWRF   TCDC  Obs_kW  n  beta  \
2016-01-01 06:30:00  2.016010e+09  7.962387   0.00000  100.0     0.0  1   0.0   
2016-01-01 07:30:00  2.016010e+09  8.077713   9.00000  100.0     0.0  1   0.0   
2016-01-01 08:30:00  2.016010e+09  8.467117  46.32202  100.0    12.0  1   0.0   
                         delta                   dtm_utc  \
2016-01-01 06:30:00 -23.058629 2016-01-01 06:30:00+00:00   
2016-01-01 07:30:00 -23.058629 2016-01-01 07:30:00+00:00   
2016-01-01 08:30:00 -23.058629 2016-01-01 08:30:00+00:00   
                                    dtm_local         ...           \
2016-01-01 06:30:00 2016-01-01 07:30:00+01:00         ...            
2016-01-01 07:30:00 2016-01-01 08:30:00+01:00         ...            
2016-01-01 08:30:00 2016-01-01 09:30:00+01:00         ...            
                                   corr1_dtm                          dtm_sun  \
2016-01-01 06:30:00 -1 days +23:45:13.666667 2016-01-01 07:12:19.401323+01:00   
2016-01-01 07:30:00 -1 days +23:45:13.666667 2016-01-01 08:12:19.401323+01:00   
2016-01-01 08:30:00 -1 days +23:45:13.666667 2016-01-01 09:12:19.401323+01:00   
                     sun_hour sun_hour_angle delta_rad  sun_hour_angle_rad  \
2016-01-01 06:30:00       7.2          -72.0 -0.402449           -1.256637   
2016-01-01 07:30:00       8.2          -57.0 -0.402449           -0.994838   
2016-01-01 08:30:00       9.2          -42.0 -0.402449           -0.733038   
                     earth_sunset_deg  earth_sunrise_deg  surface_sunset_deg  \
2016-01-01 06:30:00         68.645391         -68.645391           70.481456   
2016-01-01 07:30:00         68.645391         -68.645391           70.481456   
2016-01-01 08:30:00         68.645391         -68.645391           70.481456   
                     surface_sunrise_deg  
2016-01-01 06:30:00           -79.585047  
2016-01-01 07:30:00           -79.585047  
2016-01-01 08:30:00           -79.585047

Please notice that I have put all the dataframe columns so that you can attempt to trace back the error, but in what I am trying to do I am only interested in the last four columns, so in this part of the dataframe:

                     earth_sunset_deg  earth_sunrise_deg  surface_sunset_deg  \
2016-01-01 06:30:00         68.645391         -68.645391           70.481456   
2016-01-01 07:30:00         68.645391         -68.645391           70.481456   
2016-01-01 08:30:00         68.645391         -68.645391           70.481456   
                     surface_sunrise_deg  
2016-01-01 06:30:00           -79.585047  
2016-01-01 07:30:00           -79.585047  
2016-01-01 08:30:00           -79.585047

This is only part of the dataframe, as it contains 2 years of data. What I am trying to do is the following:

if surface_sunset_deg > earth_sunset_deg:
    sunset_deg = earth_sunset_deg
else:
    sunset_deg = surface_sunset_deg

So essentially, I am trying to iterate through all rows of the dataframe (which correspond to different timestamps), evaluate which of the 2 angles is greater (surface_sunset_deg or earth_sunset_deg) and store the one that satisfies my criterion in a new column df["sunset_deg"].

As far as I know, the most efficient way of looping over a dataframe is using the apply function, therefore what I have written is this:

df["sunset_deg"] = df.apply(lambda row: row["earth_sunset_deg"] if row["earth_sunset_deg"] < row["surface_sunset_deg"] else row["surface_sunset_earth"], axis=1)

And the error I get is this:

Traceback (most recent call last):
  File "C:\Users\Admin\Anaconda3\lib\site-packages\pandas\core\indexes\base.py", line 2483, in get_value
    return libts.get_value_box(s, key)
  File "pandas/_libs/tslib.pyx", line 923, in pandas._libs.tslib.get_value_box (pandas\_libs\tslib.c:18843)
  File "pandas/_libs/tslib.pyx", line 932, in pandas._libs.tslib.get_value_box (pandas\_libs\tslib.c:18477)
TypeError: 'str' object cannot be interpreted as an integer
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
  File "C:\Users\Admin\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2910, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-11-69be989aa737>", line 1, in <module>
    df.apply(lambda row: row["earth_sunset_deg"] if row["earth_sunset_deg"] < row["surface_sunset_deg"] else row["surface_sunset_earth"], axis=1)
  File "C:\Users\Admin\Anaconda3\lib\site-packages\pandas\core\frame.py", line 4262, in apply
    ignore_failures=ignore_failures)
  File "C:\Users\Admin\Anaconda3\lib\site-packages\pandas\core\frame.py", line 4358, in _apply_standard
    results[i] = func(v)
  File "<ipython-input-11-69be989aa737>", line 1, in <lambda>
    df.apply(lambda row: row["earth_sunset_deg"] if row["earth_sunset_deg"] < row["surface_sunset_deg"] else row["surface_sunset_earth"], axis=1)
  File "C:\Users\Admin\Anaconda3\lib\site-packages\pandas\core\series.py", line 601, in __getitem__
    result = self.index.get_value(self, key)
  File "C:\Users\Admin\Anaconda3\lib\site-packages\pandas\core\indexes\base.py", line 2491, in get_value
    raise e1
  File "C:\Users\Admin\Anaconda3\lib\site-packages\pandas\core\indexes\base.py", line 2477, in get_value
    tz=getattr(series.dtype, 'tz', None))
  File "pandas\_libs\index.pyx", line 98, in pandas._libs.index.IndexEngine.get_value
  File "pandas\_libs\index.pyx", line 106, in pandas._libs.index.IndexEngine.get_value
  File "pandas\_libs\index.pyx", line 154, in pandas._libs.index.IndexEngine.get_loc
  File "pandas\_libs\hashtable_class_helper.pxi", line 1210, in pandas._libs.hashtable.PyObjectHashTable.get_item
  File "pandas\_libs\hashtable_class_helper.pxi", line 1218, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: ('surface_sunset_earth', 'occurred at index 2016-02-02 00:30:00')

When I run the same line of code for the first 30 elemtns of the dataframe, so:

 df["sunset_deg"] = df[:30].apply(lambda row: row["earth_sunset_deg"] if row["earth_sunset_deg"] < row["surface_sunset_deg"] else row["surface_sunset_earth"], axis=1)

It is running smooth and produces the result I want. Can you please help me trace back the error? I am relatively new to Python and I have already done my best here with no success. Thank you in advance.

No need to use apply here. You can use boolean masks. df.loc[:, df["earth_sunset_deg"] < df["surface_sunset_deg"]] = df["earth_sunset_deg"] and so on. — pault
– pault, Commented Apr 5, 2018 at 15:04
Wow. Thank you so much for your help. I really overlooked it even though it was so obvious. thanks alot! — Nisfa
– Nisfa, Commented Apr 5, 2018 at 15:08

John Zwinck · Accepted Answer · 2018-04-05 15:11:22Z

2

Using apply() for this is not efficient at all. You should almost never use apply() except as a last resort. You can solve your problem much more simply:

df["sunset_deg"] = df[["earth_sunset_deg", "surface_sunset_deg"]].min(1)

Here's an alternative which might be more easily extended to different conditions:

df["sunset_deg"] = df["earth_sunset_deg"].where(df["surface_sunset_deg"] > df["earth_sunset_deg"], df["surface_sunset_deg"])

Either of these is hugely more efficient than anything using apply() (which really is just a for loop, which is dead slow).

answered Apr 5, 2018 at 15:11

John Zwinck

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Comments

Weiner Nir · Accepted Answer · 2018-04-05 15:07:20Z

The problem is that 'surface_sunset_earth' doesn't exists in the specified row. to be exact, the problem is here:

else row["surface_sunset_earth"]

you can't get the key "surface_sunset_earth" if it doesn't exists in the specified row.

Maybe you don't want to use lambda here. lambda is better for small logic, when logic gets bigger you better use a function instead.

That would be a solution:

def my_func(row):
    try:
        if row["earth_sunset_deg"] < row["surface_sunset_deg"]:
            return row["earth_sunset_deg"]  
        else:
            return row["surface_sunset_earth"]
    except KeyError:
        # Decide here what to do in case one of the keys aren't exists
        pass

df["sunset_deg"] = df[:30].apply(my_func, axis=1)

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