Random heights

mark

(5pts)

I've got a fun program on my webpage that generates random CSV data for people. You can access it via Python like so:

%matplotlib inline
import pandas as pd
df = pd.read_csv('https://www.marksmath.org/cgi-bin/random_data.csv?username=mark')
df.tail()

	first_name	last_name	age	sex	height	weight	income	activity_level
0	Donna	Dinan	35	female	65.37	164.26	1947	high
1	Antonia	Davis	39	female	64.95	140.40	2188	none
2	Stephanie	Buss	30	female	60.75	181.83	18108	high
3	Wendell	Elmore	26	male	64.68	157.90	1935	moderate
4	Nina	Mcilhinney	21	female	59.94	163.38	5675	none

Here's the cool thing - the data is randomly generated but the random number generator is seeded using the username query parameter in the URL. Thus, if I execute that command several times, I get the same result every time. That result depends upon the username, however. Thus, if you do it with your forum username, you'll get a different result. Thus, we all have our own randomly generated data file!

The problem: Using the code above with your username, generate your data file and then

1. Compute the average value of the heights in your data and
2. create a histogram of the heights.

Be sure to include both the code that you typed, as well as the results in your post.

alex

Code:

df.hist('height', edgecolor='black', grid=False,);

Histogram:

Mean: 66.207700
Mean Code:

df.height.describe()

isabel

df.hist('height', grid=False, edgecolor='black')

ben

df.hist('height', edgecolor='black', grid=False,);

zach

Mean=67.024500
Standard Deviation=3.809777

Code for the histogram:

df.hist('height', edgecolor='black', grid=False,);

sarah

%matplotlib inline
import pandas as pd
 df = pd.read_csv('https://www.marksmath.org/cgi-bin/random_data.csv?username=sarah')
df.tail()

df.hist('height', edgecolor='black', grid=False,
   );

mean: 66.266400

df.height.describe()

audrey

I generated my histogram like so:

df.hist('height', grid=False, edgecolor='black')

jordan

df.hist('height', edgecolor='black', grid=False,);

df.height.mean()

# Out:
# 66.73939999999999

lillian

I generated my histogram like so:

df.hist('height', grid='false', edgecolor='black',)

lillian

ashley

Code for histogram:

df.hist('height', edgecolor='black', grid=False,);

lillian

I generated my mean like so:

df.height.mean()

66.30110000000003

Beau

This is an example of my histogram:

 df.hist('height', edgecolor='black', grid=False);

The mean was generated this way:

 df.height.mean()

65.81690000000002

The standard deviation is:

df.height.std()

3.854679615661196