Directions are hints and tips for using pandas in an analysis environment.
dovpanda is an overlay companion for working with pandas in an analysis environment.
It is an overlay module that tries to understand what you are trying to do with your data, and helps you
make you code more concise with readable.
If you think your task is common enough, it probably is, and pandas probably has a built-in solution. dovpanda will help you find them.
The main usage of dovpanda is its hints mechanism, which is very easy and works out-of-the-box.
Just import it after you import pandas, whether inside a notebook or in a console.
import pandas as pd
import dovpandaThis is it. From now on you can expect dovpanda to come up with helpful hints while you are writing your code.
Running dovpanda in a notebook environment will display rendered dismissable html.
df = pd.DataFrame({'a':list('xxyy'),'b':[40,50,60,70], 'time':['18:02','18:45','20:12','21:50']})
df['time'] = pd.to_datetime(df.time)
df['hour'] = df.time.dt.hour
df.groupby('hour').b.sum()===== Seems like you are grouping by a column named 'hour', consider setting the your
time column as index and then use df.resample('h') =====
Out[4]:
hour
18 90
20 60
21 70
Name: b, dtype: int64
pip install dovpandadovpanda.tip() will give you a random pandas tip.
use dovpanda.set_output if you want to change output.
In [14]: dovpanda.set_output('display')
In [15]: df.iterrows()
===== iterrows is not recommended, and in the majority of cases will have better alternatives =====
Out[15]: <generator object DataFrame.iterrows at 0x110fe4318>
In [16]: dovpanda.set_output('print')
In [17]: df.iterrows()
iterrows is not recommended, and in the majority of cases will have better alternatives
Out[17]: <generator object DataFrame.iterrows at 0x112c408b8>
In [18]: dovpanda.set_output('warning')
In [19]: df.iterrows()
WARNING:dovpanda:iterrows is not recommended, and in the majority of cases will have better alternatives
Out[19]: <generator object DataFrame.iterrows at 0x110ee7e58>
In [20]: dovpanda.set_output('off')
In [21]: df.iterrows()
Out[21]: <generator object DataFrame.iterrows at 0x1047c4d68>
"dov" means bear in Hebrew 