DataFrame groupby.first() is much slower than groupby.nth(0)

[capelastegui]

Code Sample, a copy-pastable example if possible

import pandas as pd, numpy as np
df1 = pd.DataFrame({'c1':np.concatenate([np.arange(0,10000),np.arange(0,10000)]),'c2':1,'c3':'a'})

# groupby.nth(0) runs in ~11ms
%timeit x1 =df1.groupby(['c1']).nth(0, dropna='all') 
# groupby.first() runs in ~700ms
%timeit  x2 = df1.groupby(['c1']).first()

Problem description

groupby.first() takes much longer to run than groupby.nth(0), even though both operations should be equivalent. Is there any reason why the current implementation of first() shouldn't just be replaced with a call to nth()?

Output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 2.7.11.final.0
python-bits: 64
OS: Darwin
OS-release: 16.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
LOCALE: en_GB.UTF-8

pandas: 0.22.0
pytest: None
pip: 9.0.1
setuptools: 36.5.0
Cython: 0.23.4
numpy: 1.14.0
scipy: 1.0.0
pyarrow: 0.8.0
xarray: None
IPython: 5.5.0
sphinx: 1.5.3
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: 1.0.0
tables: None
numexpr: 2.5
feather: 0.4.0
matplotlib: 2.1.2
openpyxl: 2.4.1
xlrd: 0.9.4
xlwt: None
xlsxwriter: None
lxml: 3.4.4
bs4: None
html5lib: 1.0b10
sqlalchemy: 1.1.2
pymysql: None
psycopg2: 2.7.3.2 (dt dec pq3 ext lo64)
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

[jreback]

you would have to actually show the times, this is not reproducible. .first() is cythonized and should actually be faster.

In [1]: import pandas as pd, numpy as np
   ...: df1 = pd.DataFrame({'c1':np.concatenate([np.arange(0,10000),np.arange(0,10000)]),'c2':1,'c3':'a'})
   ...: 
   ...: # groupby.nth(0) runs in ~11ms
   ...: %timeit x1 =df1.groupby(['c1']).nth(0, dropna='all') 
   ...: # groupby.first() runs in ~700ms
   ...: %timeit  x2 = df1.groupby(['c1']).first()
   ...: 
6.37 ms +- 154 us per loop (mean +- std. dev. of 7 runs, 100 loops each)
2.26 ms +- 46.6 us per loop (mean +- std. dev. of 7 runs, 100 loops each)

you are probably seeing #19283 which is a fixed regression in 0.23

[gaworecki5]

I noticed this problem on a df of about 2 million rows. groupby.first() would not run at all, other aggregations like count() and sum() run in a few seconds. I did not know about nth(0) until this thread but it runs in 20 seconds. Did anyone figure out the reason this is?