Kaggle_Data Visualization of scatter plot

step0 输入和配置python库文件

import pandas as pd
pd.plotting.register_matplotlib_converters()
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns

设置代码核查

import os
if not os.path.exists("../input/candy.csv"):
    os.symlink("../input/data-for-datavis/candy.csv", "../input/candy.csv") 
from learntools.core import binder
binder.bind(globals())
from learntools.data_viz_to_coder.ex4 import *

step1 载入数据

# Path of the file to read
candy_filepath = "../input/candy.csv"

# Fill in the line below to read the file into a variable candy_data
candy_data = pd.read_csv(candy_filepath,index_col="id")

# Run the line below with no changes to check that you've loaded the data correctly
step_1.check()

step2 review数据

打印前五行数据

candy_data.head()

competitorname	chocolate	fruity	caramel	peanutyalmondy	nougat	crispedricewafer	hard	bar	pluribus	sugarpercent	pricepercent	winpercent
id
0	100 Grand	Yes	No	Yes	No	No	Yes	No	Yes	No	0.732	0.860	66.971725
1	3 Musketeers	Yes	No	No	No	Yes	No	No	Yes	No	0.604	0.511	67.602936
2	Air Heads	No	Yes	No	No	No	No	No	No	No	0.906	0.511	52.341465
3	Almond Joy	Yes	No	No	Yes	No	No	No	Yes	No	0.465	0.767	50.347546
4	Baby Ruth	Yes	No	Yes	Yes	Yes	No	No	Yes	No	0.604	0.767	56.914547

# Fill in the line below: Which candy was more popular with survey respondents:
# '3 Musketeers' or 'Almond Joy'?  (Please enclose your answer in single quotes.)
more_popular = '3 Musketeers'

# Fill in the line below: Which candy has higher sugar content: 'Air Heads'
# or 'Baby Ruth'? (Please enclose your answer in single quotes.)
more_sugar = "Air Heads"

# Check your answers
step_2.check()

Step3 The role of sugar

绘制sugarpercent和winpercent之间的散点图

# Scatter plot showing the relationship between 'sugarpercent' and 'winpercent'
plt.figure(figsize=(12,6))
sns.scatterplot(x=candy_data["sugarpercent"],y=candy_data["winpercent"])

# Check your answer
step_3.a.check()

step4 绘制回归曲线

sns.regplot()

# Scatter plot w/ regression line showing the relationship between 'sugarpercent' and 'winpercent'
plt.figure(figsize=(12,6)) # Your code here
sns.regplot(x=candy_data["sugarpercent"],y=candy_data["winpercent"])

# Check your answer
step_4.a.check()

step5 chocolate

# Scatter plot showing the relationship between 'pricepercent', 'winpercent', and 'chocolate'
sns.scatterplot(x=candy_data["pricepercent"],y=candy_data["winpercent"],hue=candy_data["chocolate"])

# Check your answer
step_5.check()

 

 

step6 investigate chocolate

创建带有两行回归行的散点图

# Color-coded scatter plot w/ regression lines
sns.lmplot(x="pricepercent",y="winpercent",hue="chocolate",data=candy_data)
sns.lmplot(x="pricepercent",y="winpercent",data=candy_data)
# Check your answer
step_6.a.check()

 

Step 7: Everybody loves chocolate

创建有类型的散点图去强调chocolate与winpercent之间的关系。把chocolate放在水平轴上，把winpercent放在y轴上。

# Scatter plot showing the relationship between 'chocolate' and 'winpercent'
sns.swarmplot(x=candy_data["chocolate"],y=candy_data["winpercent"])

# Check your answer
step_7.a.check()