Reputation: 121
In using Python Pandas on a big dataset, how can I find the index based on the value in the column, in the same row?
For example, if I have this dataset...
Column
Item 1 0
Item 2 20
Item 3 34
...
Item 1000 12
... and if I have this value 17 in one of the 1000 rows (excluding row 0) in the column, and I want to find out which one of the Item has this value 17 in the column in the same row, how can I do that?
For example, I want to find out what and where is this Item x indexed in the dataset as shown below...
Column
Item x 17
... how can I do that with Pandas, using this value 17 as reference?
Upvotes: 11
Views: 16489
Reputation: 1219
I tried one of the methods above and it did not work for me. I then put a bit more thought into it and realized I was making it more complicated than it needed to be. Here's the method I am using in my own program to get this functionality:
x = 17
df = pandas.DataFrame({'Item':[1,2,3,150],'Column':[0,20,34,17]})
response = df[df['Column'] == x].iloc[0]['Item']
print(response)
Output:
150
Upvotes: 2
Reputation: 863611
Use boolean indexing
:
df.index[df.Column == 17]
If need excluding row 0:
df1 = df.iloc[1:]
df1.index[df1.Column == 17]
Sample:
df = pd.DataFrame({'Column': {'Item 1': 0, 'Item 2': 20, 'Item 5': 12, 'Item 3': 34, 'Item 7': 17}})
print (df)
Column
Item 1 0
Item 2 20
Item 3 34
Item 5 12
Item 7 17
print (df.index[df.Column == 17])
Index(['Item 7'], dtype='object')
print (df.index[df.Column == 17].tolist())
['Item 7']
df1 = df.iloc[1:]
print (df1)
Column
Item 2 20
Item 3 34
Item 5 12
Item 7 17
print (df1.index[df1.Column == 17].tolist())
['Item 7']
Upvotes: 12
Reputation: 294526
use query
df.query('Column == 17')
use index.tolist()
to get the list of items
df.query('Column == 17').index.tolist()
Upvotes: 2