##Question
Dear all,
I have a function that synchronizes according to some specifications columns of a dataframe.
The functions works, nevertheless I was wondering how to:
- Improve performances
- Make it more pythonic
Please feel free to leave any suggestions,
Thanks.
The function, a sample and results
Function specifications
- Inputs:
df : a dataframe with columns:
[a0,...aN] : a0 to aN names can be any valid string and contains numeric values[agent,date] : are fixed names, agent contains numeric values and date contains datetime.
sync_with : The columns to synchronize with (a string or an listof string contained in [a0,..., aN] or, by default, an empty list to synchronize all the [a0,...,aN].
- Synchronization:
- Do a forward
fillna grouped by agent values.
- Drop the rows where all columns to synchronize with values are empty
- Returns : the synchronized
dataframe
Here is my function:
import pandas as pd
import numpy as np
def synchronize(df,sync_with=[]):
_df = df.copy()
if not isinstance(sync_with,list):
sync_with = [sync_with]
_fixed_cols = ['date','agent']
_fixed_cols.extend(sync_with)
_colset = [c for c in _df.columns if c not in _fixed_cols]
for ag in _df.agent.unique():
_df.loc[_df.agent==ag,_colset] = _df.loc[_df.agent==ag,_colset].fillna(method='ffill')
if sync_with:
_df = _df.dropna(how='all', subset=sync_with)
_df.loc[_df.agent==ag,:] = _df.loc[_df.agent==ag,:].fillna(method='ffill')
return _df
Sample
foo = pd.DataFrame(dict(date=pd.to_datetime(['2010', '2011', '2012', '2013', '2010', '2013', '2015', '2016']),
agent=[1,1,1,1,2,2,2,2],
_a=[1, np.nan, np.nan, 4, 5, np.nan, 7, 8],
_b=[11, 22, np.nan, np.nan, 55, np.nan, 77, np.nan],
_c=[111, np.nan, 333, np.nan, np.nan, 666, 777, np.nan]))
Results
# 1. default (10.1 ms per loop)
print(synchronize(foo))
_a _b _c agent date
0 1.0 11.0 111.0 1 2010-01-01
1 1.0 22.0 111.0 1 2011-01-01
2 1.0 22.0 333.0 1 2012-01-01
3 4.0 22.0 333.0 1 2013-01-01
4 5.0 55.0 NaN 2 2010-01-01
5 5.0 55.0 666.0 2 2013-01-01
6 7.0 77.0 777.0 2 2015-01-01
7 8.0 77.0 777.0 2 2016-01-01
# 2. sync with one column (54.9 ms per loop)
print(synchronize(foo,'_c'))
_a _b _c agent date
0 1.0 11.0 111.0 1 2010-01-01
2 1.0 22.0 333.0 1 2012-01-01
5 NaN NaN 666.0 2 2013-01-01
6 7.0 77.0 777.0 2 2015-01-01
# 3. sync with two columns (53.4 ms per loop)
print(synchronize(foo,['_a','_b'))
_a _b _c agent date
0 1.0 11.0 111.0 1 2010-01-01
1 1.0 22.0 111.0 1 2011-01-01
3 4.0 22.0 333.0 1 2013-01-01
4 5.0 55.0 NaN 2 2010-01-01
6 7.0 77.0 777.0 2 2015-01-01
7 8.0 77.0 777.0 2 2016-01-01
