Reputation: 663
I have a column that's unorganized like this;
Name
Jack
James
Riddick
Random value
Another random value
What I'm trying to do is get only the names from this column, but struggling to find a way to differentiate real names to random values. Fortunately the names are all together, and the random values are all together as well. The only thing I can do is iterate the rows until it gets to 'Random value' and then break off.
I've tried using lambda's for this but with no success as I don't think there's a way to break. And I'm not sure how comprehension could work in this case.
Here's the example I've been trying to play with;
df['Name'] = df['Name'].map(lambda x: True if x != 'Random value' else break)
But the above doesn't work. Any suggestions on what could work based on what I'm trying to achieve? Thanks.
Upvotes: 1
Views: 1360
Reputation: 7903
Find index of row containing 'Random value':
index_split = df[df.Name == 'Random value'].index.values[0]
Save your random values column for use later if you want:
random_values = df.iloc[index_split+1:,].values[0]
Remove random values from the Names column:
df = df[0:index_split]
Upvotes: 1