Describe the bug
Non-selected fields become NaN but all fields are still present in the dataframe - this is different from the example output in the docs.
To Reproduce
Run the code from the "Fields Selection" section of this page:
from gs_quant.data import Dataset
from datetime import date
weather_ds = Dataset('WEATHER')
data_frame = weather_ds.get_data(date(2016, 1, 1), date(2016, 1, 2), city=["Boston"], fields=['maxTemperature', 'minTemperature'])
print(data_frame)
Expected behavior
Returns:
city date maxTemperature minTemperature
0 Boston 2016-01-01 41.0 33.0
1 Boston 2016-01-02 40.0 31.0
Actual behavior
Returns:
city maxTemperature minTemperature dewPoint windSpeed
date
2016-01-01 Boston 41.0 33.0 NaN NaN \
2016-01-02 Boston 40.0 31.0 NaN NaN
precipitation snowfall pressure updateTime
date
2016-01-01 NaN NaN NaN NaN
2016-01-02 NaN NaN NaN NaN
Describe the bug Non-selected fields become NaN but all fields are still present in the dataframe - this is different from the example output in the docs.
To Reproduce Run the code from the "Fields Selection" section of this page:
Expected behavior Returns:
Actual behavior Returns:
Systems setup: