CODEWITHSUNDEEP
pythonpython-3.xlistpandasdataframe
Eric John E.
Eric John E.

Reputation: 73

python 3.5 pandas read excel and convert to a list

I have an excel file with a data as shown below:

 Col_Title1 | Col_Title2 | Col_Title3 | Label
 Row11      | Row12      | Row13      | 1
 Row21      | Row22      | Row23      | 2
 Row31      | Row32      | Row33      | 3

Using pandas, I read this excel file like this:

import pandas as pd

df = pd.read_excel(FOLDER_DOWNLOAD_LOCATION + '1.xlsx', sheet_name='Sheet1')

Now, I wish to output the following list using the df :

1. [[Row11, Row12, Row13], [Row21, Row22, Row23], [Row31, Row32, Row33]]

2. [1,2,3]

I don't know the efficient way or a good technique to attain those type of list outputs.

P.S. I'm a newbie in programming & sorry for asking this type of question.

Upvotes: 0

Views: 18393

Answers (2)

jpp
jpp

Reputation: 164613

One way is to use slicing, assuming you know the order of your columns in advance.

df_values = df.values

# [['Row11' 'Row12' 'Row13' 1]
#  ['Row21' 'Row22' 'Row23' 2]
#  ['Row31' 'Row32' 'Row33' 3]]

Then slice as appropriate:

df_values[:, :-1].tolist()

# [['Row11', 'Row12', 'Row13'],
#  ['Row21', 'Row22', 'Row23'],
#  ['Row31', 'Row32', 'Row33']]

df_values[:, -1].tolist()

# [1, 2, 3]

Upvotes: 3

jezrael
jezrael

Reputation: 862396

I believe you need remove Label column, convert to numpy array by values and then to list:

a = df.drop('Label', 1).values.tolist()
print (a)
[['Row11', 'Row12', 'Row13'], ['Row21', 'Row22', 'Row23'], ['Row31', 'Row32', 'Row33']]

b = df['Label'].values.tolist()
print (b)
[1, 2, 3]

Upvotes: 3

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