Case Study (Wine Quality) : Appending Data

new_dataframe = first_dataframe.append (second_dataframe, ignore_index=True)

* new_dataframe: df_wine
* first_dataframe: df_red
* second_dataframe: df_white

df_wine = df_red.append(df_white, ignore_index=True)

Loading Data (Red Wine Dataset & White Wine Dataset)

In [3]:
import pandas as pd
import numpy as np

df_red = pd.read_csv('red.csv')

df_white = pd.read_csv('white.csv')

Creating a new column 'color' in both datasets before appending data

In [4]:
df_red.loc[:,'color'] = 'red'

df_white.loc[:,'color'] = 'white'

Appending dataset white wine to red wine

In [6]:
df_wine = df_red.append(df_white, ignore_index=True)

df_wine
Out[6]:
fixed_acidity volatile_acidity citric_acid residual_sugar chlorides free_sulfur_dioxide total_sulfur_dioxide density ph sulphates alcohol quality color
0 7.4 0.70 0.00 1.9 0.076 11.0 34.0 0.99780 3.51 0.56 9.4 5 red
1 7.8 0.88 0.00 2.6 0.098 25.0 67.0 0.99680 3.20 0.68 9.8 5 red
2 7.8 0.76 0.04 2.3 0.092 15.0 54.0 0.99700 3.26 0.65 9.8 5 red
3 11.2 0.28 0.56 1.9 0.075 17.0 60.0 0.99800 3.16 0.58 9.8 6 red
4 7.4 0.70 0.00 1.9 0.076 11.0 34.0 0.99780 3.51 0.56 9.4 5 red
... ... ... ... ... ... ... ... ... ... ... ... ... ...
6492 6.2 0.21 0.29 1.6 0.039 24.0 92.0 0.99114 3.27 0.50 11.2 6 white
6493 6.6 0.32 0.36 8.0 0.047 57.0 168.0 0.99490 3.15 0.46 9.6 5 white
6494 6.5 0.24 0.19 1.2 0.041 30.0 111.0 0.99254 2.99 0.46 9.4 6 white
6495 5.5 0.29 0.30 1.1 0.022 20.0 110.0 0.98869 3.34 0.38 12.8 7 white
6496 6.0 0.21 0.38 0.8 0.020 22.0 98.0 0.98941 3.26 0.32 11.8 6 white

6497 rows × 13 columns

Save Combined Dataset (df_wine)

- Exporting (df_wine) to csv file called 'wine.csv'
In [4]:
df_wine.to_csv('wine.csv', index = False)