Reputation: 379
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.
Upvotes: 0
Views: 2840
Reputation: 249243
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).
Upvotes: 2
Reputation: 1475
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)
Upvotes: 0