Dropping Columns in a Dataframe based on if they have a particular letter in the title

Question

Is there a way to drop columns in a Dataframe with column names having a particular letter as I wasn't able to find any information on this? I currently have the following code, which creates a dataframe that look as follows:

   dates       BETA0        BETA1        BETA2        BETA3 SVEN1F01  \
0    2015-06-17  5.06404203  -4.82869948  -4.40587372  -4.63038436   1.0273   
1    2015-06-16  5.21759473  -5.10202006  -4.06913368  -5.23883082   1.1137   
2    2015-06-15  5.25192065  -5.08400946  -4.34674471  -5.25279453   1.1193   
3    2015-06-12  5.38755314  -5.17612353  -4.53605822  -5.62290340   1.1443 

I want to drop all column headers having the letter F in them. I was planning on doing it using df.drop([df.columns[[column_names]]], axis=1), but there are so many that I was wondering if there is an easier way to do this.

from bs4 import BeautifulSoup
import urllib.request
import requests
from itertools import islice
import pandas as pd

r = requests.get(
    "http://www.federalreserve.gov/econresdata/researchdata/feds200628_1.html")
soup = BeautifulSoup(r.content)

data = soup.find('table', attrs={'rules': 'all'})
h = data.find_all("th", scope="col") #Issue
final = [[t.th.text] + [ele.text for ele in t.find_all("td")] for t in h[-1].find_all_next("tr")]
headers = [th.text for th in h]

headers.insert(0,"Date")
df = pd.DataFrame(final,columns=headers)

print(df)

Thank You

Answer 1

df_filtered = df[list(filter(lambda x: "F" not in x, df.columns))]