I have a pandas Dataframe which has a couple of columns. I want to get the first 3 elements out of the Information Column based on a value in Protocol.
For example: I want the first 3 elements in Information IF the protocol is TCP.
Using below code I can separate the columns needed for my operation. But I have no clue how to adapt the next piece of code to this.
chunk[['Protocol', 'Information']] = chunk[['Protocol', 'Information']]
EDIT:
I wish to update the values. Not separate them.
You can use something like this:
import pandas
data = data = {'Name':['first', 'second', 'third', 'fourth'],
'Age':[27, 27, 22, 32],
'Address':['New York', 'ABC', 'XYZ', 'Nowhere'],
'Qualification':['Msc', 'MA', 'MA', 'Phd']}
# Make a dataframe object
df = pandas.DataFrame(data)
# Your condition
# for example we want to get the rows with `Qualitication=='MA'
is_MA_qualified = df['Qualification'] == 'MA'
# Now to filter your data
MA_qualified = df[is_MA_qualified]
# You can use `head(n)` to get first three rows
first_three_MA_qualified = MA_qualified.head(3)
# And finally, to get any desired columns
first_three_MA_qualified[['Age','Address']]
UPDATE: to update cells, you can iterate over rows and then change the values of the cells that fulfill the condition:
...
for index, row in df.iterrows():
if row['Age'] >= 18:
df.at[index, 'Qualification'] = 'Verified'
