Agfdhyk

I am trying to clean a dataframe using Pandas and I need to extract out those rows with the identifier, name, and number of points, and put them in new columns named named identifier, name, and num_pts.

I need to do boolean indexing on the new columns after.

I tried creating a new column based off another column like this
hurricane_df['new_col'] = hurricane_df['col'] but when trying to index the new_col it would also index the original col.

This is what I currently have

This is what the data has to look like after

Thank you for any help

import os

import pandas as pd

from urllib.request import urlretrieve

url = "https://www.nhc.noaa.gov/data/hurdat/hurdat2-1851-2017-050118.txt"

local_fname = "hurdat2.txt"

if not os.path.exists("hurdat2.txt"):

    urlretrieve(url, local_fname)





low_memory=False

hurricane_df = pd.read_csv("hurdat2.txt",engine='python', 

delim_whitespace=True,names = 

['date','time','record_id','status','latitude','longitude','max_wind',

'min_pressure','ne34ktr','se34ktr','sw34ktr','nw34ktr','ne50ktr','se50ktr',

'sw50ktr','nw50ktr','ne64ktr','se64ktr','sw64ktr','nw64ktr']

,header = None)



hurricane_df["identifier"] = hurricane_df["date"].copy()

hurricane_df[(hurricane_df['identifier'].str.contains('AL'))]

edit: What I ultimately want to do is toe xtract out those rows with the identifier, name, and number of points, and put them in new columns named named identifier, name, and num_pts. So I started with taking the date column and adding those values into the identifier column and parsing the identifier column with strings that only begin with AL to get the identifier rows only.

What happened though was that the date column was still changing.

After I do that I want to fill that in with the tracking points, remove the rows with just the identifier information (that goes in the new date column which I would extract from the date as well, negating the AL(~) to get just the identifier information and then reorder the columns to the front of the dataframe (df[['c4','c5','c1','c2','c3']).

This only partially answers your question, but I hope it will be helpful:

I tried creating a new column based off another column like this hurricane_df['new_col'] = hurricane_df['col'] but when trying to index the new_col it would also index the original col.

To avoid this error, use

hurricane_df["new_column"] = hurricane_df["old_column"].copy()

In Python, doing variable_a = variable_b will not copy the value of variable_b and assign it to variable_a. It will just create a new name that is bound to the same object bound to variable_a.

For instance, if you do

a = 2

b = a

a = a + 1

print(b)

You'll get a 3. This is called "passing by reference"; other languages have "passing by value".

If you explain in more detail what your ultimate goal is we might find a way to help you (adding the rows it contains to a dataframe as new columns sounds a bit odd, and maybe there is a better way to do what you wanted to do in the first place).