Groupby
by level of MultiIndex
with rolling
duplicate index level.
df = pd.DataFrame(data=[[1, 1, 10, 20], [1, 2, 30, 40], [1, 3, 50, 60],
[2, 1, 11, 21], [2, 2, 31, 41], [2, 3, 51, 61]],
columns=['id', 'date', 'd1', 'd2'])
df.set_index(['id', 'date'], inplace=True)
print (df)
d1 d2
id date
1 1 10 20
2 30 40
3 50 60
2 1 11 21
2 31 41
3 51 61
Double id
level.
df1 = df.d1.groupby(level='id').rolling(window=2).sum()
print(df1)
id id date
1 1 1 NaN
2 40.0
3 80.0
2 2 1 NaN
2 42.0
3 82.0
Name: d1, dtype: float64
Solution with apply
works nice.
df2 = df.groupby(level='id').d1.apply(lambda x: x.rolling(window=2).sum())
print(df2)
id date
1 1 NaN
2 40.0
3 80.0
2 1 NaN
2 42.0
3 82.0
Name: d1, dtype: float64
print (pd.show_versions())
INSTALLED VERSIONS
------------------
commit: None
python: 3.5.1.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 42 Stepping 7, GenuineIntel
byteorder: little
LC_ALL: None
LANG: sk_SK
LOCALE: None.None
pandas: 0.19.2
nose: 1.3.7
pip: 8.1.1
setuptools: 20.3
Cython: 0.23.4
numpy: 1.11.0
scipy: 0.17.0
statsmodels: 0.6.1
xarray: None
IPython: 4.1.2
sphinx: 1.3.1
patsy: 0.4.0
dateutil: 2.5.1
pytz: 2016.2
blosc: None
bottleneck: 1.0.0
tables: 3.2.2
numexpr: 2.5.1
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: 0.9.4
xlwt: 1.0.0
xlsxwriter: 0.8.4
lxml: 3.6.0
bs4: 4.4.1
html5lib: 0.999
httplib2: None
apiclient: None
sqlalchemy: 1.0.12
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.39.0
pandas_datareader: 0.2.1
None
Comment From: jreback
duplicate of #14013
Comment From: leeprevost
I think this bug has been reintroduced in 1.3.5. I'm getting duplicate index values even with group_keys=False.