熊猫DataFrame浮动格式

Question

I have a Pandas DataFrame of survey responses that I'm aggregating to averaged scores and outputting to HTML. My current code looks like this:

import pandas as pd
import numpy as np

df = pd.read_csv('survey_scores.csv', header=0)
np.round(pd.DataFrame(df.groupby('question_number').aggregate('mean').score).transpose(), 2).to_html()

It takes a DataFrame that looks kinda like this in csv...

response_number, question_number, score
1, 1, 3.0
1, 2, 4.0
1, 3, 4.0
2, 1, 4.0
2, 2, 4.0
2, 3, 1.0

And it outputs the averaged scores to an HTML table that formats the score values like this:

3.5, 4, 2.5

However, I'm trying to get the output to force each number to display two digits after the decimal point. I got it to round to two decimal points, but I'm having difficulty getting my output to format the values like this:

3.50, 4.00, 2.50

How can I get these values formatted to two decimal places?

Answer 1

I've solved the problem. pandas.DataFrame.to_html() can format floats.

import pandas as pd
import numpy as np

df = pd.read_csv('survey_scores.csv', header=0)
np.round(pd.DataFrame(df.groupby('question_number').aggregate('mean').score).transpose(), 2).to_html(float_format=lambda x: '%.2f' % x)

Answer 2

df.groupby('question_number').aggregate('mean').score.transpose()\
.apply(lambda x: '{0:.2f}'.format(x))

Out[422]: 
question_number
1                  3.50
2                  4.00
3                  2.50
Name: score, dtype: object

Answer 3

Assuming you have float values, format them to 2 digits.

>>>　print("%.2f" % 2.5)
2.50