From 53f431a592450446497c9f32774e6b0daa2c1db5 Mon Sep 17 00:00:00 2001
From: LAKSHAY AGGARWAL <48948478+LakshayAggarwal25@users.noreply.github.com>
Date: Tue, 3 Aug 2021 19:36:40 +0530
Subject: [PATCH] Updated table visualization

Updated table visualization for output table  on line number 298
---
 7-TimeSeries/2-ARIMA/README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/7-TimeSeries/2-ARIMA/README.md b/7-TimeSeries/2-ARIMA/README.md
index d54a781be..97d0c49ad 100644
--- a/7-TimeSeries/2-ARIMA/README.md
+++ b/7-TimeSeries/2-ARIMA/README.md
@@ -295,7 +295,7 @@ Walk-forward validation is the gold standard of time series model evaluation and
     eval_df.head()
     ```
 
-    ```output
+    Output
     |     |            | timestamp | h   | prediction | actual   |
     | --- | ---------- | --------- | --- | ---------- | -------- |
     | 0   | 2014-12-30 | 00:00:00  | t+1 | 3,008.74   | 3,023.00 |
@@ -303,7 +303,7 @@ Walk-forward validation is the gold standard of time series model evaluation and
     | 2   | 2014-12-30 | 02:00:00  | t+1 | 2,900.17   | 2,899.00 |
     | 3   | 2014-12-30 | 03:00:00  | t+1 | 2,917.69   | 2,886.00 |
     | 4   | 2014-12-30 | 04:00:00  | t+1 | 2,946.99   | 2,963.00 |
-    ```
+    
 
     Observe the hourly data's prediction, compared to the actual load. How accurate is this?