application_vnd.jupyter.stderr_output_2.png text_plain_output_3.png text_plain_output_1.png
import numpy as np

import pandas as pd

import pandas as pd
import numpy as np
import seaborn as sns
train_types = {'Agencia_ID': np.uint16, 'Ruta_SAK': np.uint16, 'Cliente_ID': np.uint32, 'Producto_ID': np.uint16, 'Demanda_uni_equil': np.uint32}
test_types = {'Agencia_ID': np.uint16, 'Ruta_SAK': np.uint16, 'Cliente_ID': np.uint32, 'Producto_ID': np.uint16, 'id': np.uint32}
df_train = pd.read_csv('../input/train.csv', usecols=train_types.keys(), dtype=train_types)
df_test = pd.read_csv('../input/test.csv', usecols=test_types.keys(), dtype=test_types)
df_client = pd.read_csv('../input/cliente_tabla.csv')
df_product = pd.read_csv('../input/producto_tabla.csv')
df_town = pd.read_csv('../input/town_state.csv')

print('Train Data\n', df_train.head(1), '\n')
print('Test Data\n', df_test.head(1), '\n')
print('Client Data\n', df_client.head(1), '\n')
print('Product Data\n', df_product.head(1), '\n')
print('Town Data\n', df_town.head(1), '\n')