Scatterplot and boxplot using matplotlib

In [2]:

import pandas as pd
import matplotlib.pyplot as plt

#Read the data
df = pd.read_csv(r'bodyfat.csv')  

EDA (Exploratory Data Analysis)¶

In [4]:

df.head()

Out[4]:

	Density	BodyFat	Age	Weight	Height	Neck	Chest	Abdomen	Hip	Thigh	Knee	Ankle	Biceps	Forearm	Wrist
0	1.0708	12.3	23	154.25	67.75	36.2	93.1	85.2	94.5	59.0	37.3	21.9	32.0	27.4	17.1
1	1.0853	6.1	22	173.25	72.25	38.5	93.6	83.0	98.7	58.7	37.3	23.4	30.5	28.9	18.2
2	1.0414	25.3	22	154.00	66.25	34.0	95.8	87.9	99.2	59.6	38.9	24.0	28.8	25.2	16.6
3	1.0751	10.4	26	184.75	72.25	37.4	101.8	86.4	101.2	60.1	37.3	22.8	32.4	29.4	18.2
4	1.0340	28.7	24	184.25	71.25	34.4	97.3	100.0	101.9	63.2	42.2	24.0	32.2	27.7	17.7

In [5]:

df.columns

Out[5]:

Index(['Density', 'BodyFat', 'Age', 'Weight', 'Height', 'Neck', 'Chest', 'Abdomen', 'Hip', 'Thigh', 'Knee', 'Ankle', 'Biceps', 'Forearm', 'Wrist'], dtype='object')

In [7]:

type(df)

Out[7]:

pandas.core.frame.DataFrame

In [6]:

type(['BodyFat', 'Age'])

Out[6]:

list

In [8]:

cols = ['BodyFat', 'Age']
data = df[cols]

In [9]:

type(data)

Out[9]:

pandas.core.frame.DataFrame

In [10]:

d = df['Age']

In [12]:

type(d) # Series: One-dimensional ndarray with axis labels (including time series)

Out[12]:

pandas.core.series.Series

In [13]:

data.head()

Out[13]:

	BodyFat	Age
0	12.3	23
1	6.1	22
2	25.3	22
3	10.4	26
4	28.7	24

In [14]:

data.corr()

Out[14]:

	BodyFat	Age
BodyFat	1.000000	0.291458
Age	0.291458	1.000000

Pearson's Correlation Coefficient: 
summation((xi - xmean)(yi - ymean)) / N.stdx.stdy

It goes from -1 to 1.
Negative: it one value will increase, other value will decrease
Positive: both rise and fall together

In [16]:

#Adding title
plt.title("Box Plot using matplotlib")
# Plotting the box plot
plt.boxplot(data,patch_artist=(True))

plt.xticks([1,2], ["BodyFat", "Age"])

# plt.xticks(ticks, labels=None, *, minor=False, **kwargs)
# ticks: list of floats: List of tick locations. The axis Locator is replaced by a FixedLocator.
# labels: List of tick labels. If not set, the labels are generated with the axis tick Formatter.

#Showing the plot
plt.show()

In [17]:

import pandas as pd
import matplotlib.pyplot as plt

#Read the data
df = pd.read_csv(r'bodyfat.csv')  

#Adding title
plt.title("Scatter Plot using matplotlib")
#Plotting the data

plt.xlabel ('BodyFat')
plt.ylabel ('Age')
    
plt.scatter(df['BodyFat'], df['Age'],alpha=0.8)
plt.show()

In [ ]:

Tags: Data Mining,Technology,