I have a dataset that looks like this
43466 1323.507803
43467 1396.948621
43468 1481.437362
43469 1611.111671
43470 1379.217261
43471 1425.450351
I am trying to loop through the dataset with Python Pandas and set x and y axis for each day to look at the last 30, here I use a smaller set for shorter explanation - last 3 days
I have itertupled through the rows correctly but I am not sure why this is not working.
I am using
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
dataset = pd.read_csv('~/Desktop/test2.csv')
df = pd.DataFrame(dataset)
for row in dataset.head(2).itertuples():
#print(row.Date)
print(dataset.loc[dataset["Date"]==row.Date].tail(5))
What I currently get is:
Date Usage
0 43466.0 1323.507803
Date Usage
1 43467.0 1396.948621
If I loop through the row - I am expecting each print out to start where the date is == to the row.Date being looped. The final print should look like this
row index 0 print
43466 1323.507803
row index 1 print
43466 1323.507803
43467 1396.948621
row index 2 print
43466 1323.507803
43467 1396.948621
43468 1481.437362
. . . . . all the way to row index 5 print
43466 1323.507803
43467 1396.948621
43468 1481.437362
43469 1611.111671
43470 1379.217261
43471 1425.450351