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ViewsExtracting specific columns from pandas.dataframe
I'm trying to use python to read my csv file extract specific columns to a pandas.dataframe and show that dataframe. However, I don't see the data frame, I receive Series([], dtype: object) as an output. Below is the code that I'm working with:
My document consists of:
product sub_product issue sub_issue consumer_complaint_narrative
company_public_response company state zipcode tags
consumer_consent_provided submitted_via date_sent_to_company
company_response_to_consumer timely_response consumer_disputed?
complaint_id
I want to extract : sub_product issue sub_issue consumer_complaint_narrative
import pandas as pd
df=pd.read_csv("C:\\....\\consumer_complaints.csv")
df=df.stack(level=0)
df2 = df.filter(regex='[B-F]')
df[df2]
3 answers
Answer question0
import pandas as pd
input_file = "C:\\....\\consumer_complaints.csv"
dataset = pd.read_csv(input_file)
df = pd.DataFrame(dataset)
cols = [1,2,3,4]
df = df[df.columns[cols]]
Here specify your column numbers which you want to select. In dataframe, column start from index = 0
cols = []
You can select column by name wise also. Just use following line
df = df[["Column Name","Column Name2"]]
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A simple way to achieve this would be as follows:
df = pd.read_csv("C:\\....\\consumer_complaints.csv")
df2 = df.loc[:,'B':'F']
Hope that helps.
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This worked for me, using slicing:
df=pd.read_csv
df1=df[n1:n2]
Where $n1<n2# are both columns in the range, e.g:
if you want columns 3-5, use
df1=df[3:5]
For the first column, use
df1=df[0]
Though not sure how to select a discontinuous range of columns.
We can also use i.loc. Given data in dataset2:
dataset2.iloc[:3,[1,2]]
Will spit out the top 3 rows of columns 2-3 (Remember numbering starts at 0)
Then dataset2.iloc[:3,[1,2]] spits out
