Web抓取到数据框。 添加列时出现错误

Question

My error: "list indices must be integers or slices, not list"

I know that there are seemingly endless amounts of posts related to that error, but I've searched and can't figure it out. If there is a solution that I missed and will help me, please let me know.

Anyways...

I'm using pandas to web scrape stock information into a dataframe, then add two calculated columns to the end:

1. to calculate the price
2. another unrelated calc

The issues I'm seeing is when I try to add the first calculated column (the last bit of code):

# Dependencies
from bs4 import BeautifulSoup
import requests
import pandas as pd

url = 'http://www.dividend.com/dividend-stocks/preferred-dividend-stocks.php#stocks&sort_name=Symbol&sort_order=ASC&page=1'
tables = pd.read_html(url)
tables

type(tables)
type(tables[0])
tables[0].head()

tables['Perp Value'] = (1/(tables['Dividend Yield']/100))*tables['Annual Dividend']
tables[0].head()

When I try to add the column 'Perp Value' I get the error. What do I need to add to be able to do my calc?

For reference, the unformatted data looks like:

\\nDividend Yield\\n \\nCurrent Price\\n \\nAnnual Dividend\\n \\n52-Week High\\n \\ 0 8.04% $25.65 $2.06 25.98
1 7.61% $25.47 $1.94 25.95
2 6.66% $25.82 $1.72 28.80
3 7.47% $25.95 $1.94 26.87
4 5.78% $25.72 $1.49 28.99
5 8.06% $26.20 $2.11 26.00
6 7.72% $23.87 $1.84 0.00
7 7.75% $23.80 $1.84 0.00
8 7.80% $24.05 $1.88 0.00
9

Answer 1

Try this:

Find column names:

list(tables[0])

['\nStock Symbol\n',
'\nCompany Name\n',
'\nDividend Yield\n',
'\nCurrent Price\n',
'\nAnnual Dividend\n',
'\n52-Week High\n',
'\n52-Week Low\n']

Clean data and convert to numeric:

a = tables[0][list(tables[0])[4]]
a = a.replace('[\$,]', '', regex=True).astype(float)
b = tables[0][list(tables[0])[2]]
b = b.replace('[\%,]', '', regex=True).astype(float)

Output:

(1/a/100)*b

0     0.039029
1     0.039227
2     0.038721
3     0.038505
4     0.038792
5     0.038199
6     0.041957
7     0.042120
8     0.041489
9     0.041649
10    0.038594
11    0.039053
12    0.038795
13    0.037853
14    0.037546
15    0.039100
16    0.039320
17    0.039898
18    0.038431
19    0.040290
dtype: float64

Assign:

tables[0]["Perp Value"] = (1/a/100)*b