Your goal is to predict the total_cases label for each (ID) in the test set. There are two cities, San Juan and Iquitos, with test data for each city spanning 5 and 3 years respectively. You will make one submission that contains predictions for both cities. The data for each city have been concatenated along with a city column indicating the source: sj for San Juan and iq for Iquitos. Throughout, missing values have been filled as NaNs.
city – City abbreviations: sj for San Juan and iq for Iquitosmonth – Month of the yearstation_max_temp_c – Maximum temperaturestation_min_temp_c – Minimum temperaturestation_avg_temp_c – Average temperaturestation_precip_mm – Total precipitationstation_diur_temp_rng_c – Diurnal temperature rangeprecipitation_amt_mm – Total precipitationreanalysis_sat_precip_amt_mm – Total precipitationreanalysis_dew_point_temp_k – Mean dew point temperaturereanalysis_air_temp_k – Mean air temperaturereanalysis_relative_humidity_percent – Mean relative humidityreanalysis_specific_humidity_g_per_kg – Mean specific humidityreanalysis_precip_amt_kg_per_m2 – Total precipitationreanalysis_max_air_temp_k – Maximum air temperaturereanalysis_min_air_temp_k – Minimum air temperaturereanalysis_avg_temp_k – Average air temperaturereanalysis_tdtr_k – Diurnal temperature rangendvi_se – Pixel southeast of city centroidndvi_sw – Pixel southwest of city centroidndvi_ne – Pixel northeast of city centroidndvi_nw – Pixel northwest of city centroid