text_plain_output_1.png
import pandas as pd

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

df_train = pd.read_csv('../input/jane-street-market-prediction/train.csv')
df_feature = pd.read_csv('../input/jane-street-market-prediction/features.csv')
df_test = pd.read_csv('../input/jane-street-market-prediction/example_test.csv')
df_sub = pd.read_csv('../input/jane-street-market-prediction/example_sample_submission.csv')

(df_train.shape, df_feature.shape, df_test.shape, df_sub.shape)

df_train.isnull().sum()

df_train = df_train.dropna(axis=0, subset=['feature_129'])
df_train = df_train.dropna(axis=0, subset=['feature_127'])
df_train = df_train.dropna(axis=0, subset=['feature_125'])
df_train = df_train.dropna(axis=0, subset=['feature_121'])
df_train = df_train.dropna(axis=0, subset=['feature_123'])
df_train = df_train.dropna(axis=0, subset=['feature_118'])
df_train = df_train.dropna(axis=0, subset=['feature_118'])
df_train = df_train.dropna(axis=0, subset=['feature_117'])
df_train = df_train.dropna(axis=0, subset=['feature_110'])
df_train = df_train.dropna(axis=0, subset=['feature_93'])
df_train = df_train.dropna(axis=0, subset=['feature_59'])
df_train = df_train.dropna(axis=0, subset=['feature_58'])
df_train = df_train.dropna(axis=0, subset=['feature_56'])
df_train = df_train.dropna(axis=0, subset=['feature_55'])
df_train = df_train.dropna(axis=0, subset=['feature_45'])
df_train = df_train.dropna(axis=0, subset=['feature_31'])
df_train = df_train.dropna(axis=0, subset=['feature_21'])
df_train = df_train.dropna(axis=0, subset=['feature_3'])
df_train.shape

df_train.isnull().sum()