Kaggle competition: Lyft Motion Prediction for Autonomous Vehicles
<SOS> metric: PostProcessorKernel Kaggle data source: lyft-motion-prediction-autonomous-vehicles<count_values>
df_train['roadKills'].value_counts()<count_values>
df_train['teamKills'].value_counts()<count_values>
df_train['headshotKills'].value_counts()<count_values>
df_train['vehicleDestroys'].value_counts()<sort_values>
total = df_train.isnull().sum().sort_values(ascending=False)
 percent =(df_train.isnull().sum() /df_train.isnull().count() ).sort_values(ascending=False)
 missing_data = pd.concat([total, percent], axis=1, keys=['Total', 'Percent'])
 missing_data.head(20 )<sort_values>
total = df_test.isnull().sum().sort_values(ascending=False)
 percent =(df_test.isnull().sum() /df_test.isnull().count() ).sort_values(ascending=False)
 missing_data = pd.concat([total, percent], axis=1, keys=['Total', 'Percent'])
 missing_data.head(20 )<filter>
<feature_engineering><EOS> 
SUBMISSION_FOLDER = '.. /input/resnet4days'
SUBMISSION_FILE = 'resnet50-10000000.csv'
submissions = pd.read_csv(f"{SUBMISSION_FOLDER}/{SUBMISSION_FILE}")
 submissions.to_csv("submission.csv", index=False )