I have this DataFrame and would like to separate the column from the date how do I do this?
Data e Hora Consumo(litros) Valor Acumulado
0 2017-08-21 20:00:00 65 65
1 2017-08-21 21:00:00 81 146
2 2017-08-21 22:00:00 10 156
You should first transform the Data e Hora column to datetime
df['Data e Hora'] = pd.to_datetime(df['Data e Hora'])
to create the columns by using the dt.strftime convert the value of the Data e Hora column to a string in date format .
# Coluna 'Data'
df['Data'] = df['Data e Hora'].dt.strftime('%Y-%m-%d')
# Coluna 'Hora'
df['Hora'] = df['Data e Hora'].dt.strftime('%H:%M:%S')
Now it has the result:
Data e Hora Consumo(litros) ... Data Hora
0 2017-08-21 20:00:00 65 ... 2017-08-21 20:00:00
1 2017-08-21 21:00:00 81 ... 2017-08-21 21:00:00
2 2017-08-21 22:00:00 10 ... 2017-08-21 22:00:00
If you want to remove the Data e Hora column and sort the columns by placing the Data column and the Hora column at startup:
# Remove a coluna 'Data e Hora'
del df['Data e Hora']
# Ordena as colunas
df = df[['Data', 'Hora', 'Consumo(litros)', 'Valor Acumulado']]
The result now is:
Data Hora Consumo(litros) Valor Acumulado
0 2017-08-21 20:00:00 65 65
1 2017-08-21 21:00:00 81 146
2 2017-08-21 22:00:00 10 156
import pandas as pd
df = pd.read_csv('DataFrame.csv', delimiter=";");
df['Data e Hora'] = pd.to_datetime(df['Data e Hora'])
df['Data'] = df['Data e Hora'].dt.strftime('%Y-%m-%d')
df['Hora'] = df['Data e Hora'].dt.strftime('%H:%M:%S')
del df['Data e Hora']
df = df[['Data', 'Hora', 'Consumo(litros)', 'Valor Acumulado']]
print(df)