pandas实例-merge-House Market

继续前面的练习，之前的文章参考：

• pandas实例-了解你的数据-Chipotle
• pandas实例-筛选与排序-Chipotle
• pandas实例-数据可视化-Chipotle
• pandas实例-了解你的数据-Occupation
• pandas实例-筛选与过滤-Euro 12
• pandas实例-筛选与过滤-Fictional Army
• pandas实例-聚合-Alcohol Consumption
• pandas实例-聚合-Occupation
• pandas实例-聚合-Regiment
• pandas实例-Apply-Student Alcohol Consumption
• pandas实例-Apply-Crime Rates
• pandas实例-Merge-MPG Cars
• pandas实例-Merge-Fictitious Names

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这次的数据集，同样需要手动来构造

1. Create 3 differents Series, each of length 100, as follows:

1. The first a random number from 1 to 4
2. The second a random number from 1 to 3
3. The third a random number from 10,000 to 30,000

s1 = pd.Series(np.random.randint(low=1 , high=5 , size=100))
s2 = pd.Series(np.random.randint(low=1 , high=4 , size=100))
s3 = pd.Series(np.random.randint(low=10000 , high=30001 , size=100))

2. Let's create a DataFrame by joinning the Series by column

把3个series拼接起来，可以使用昨天的函数：concat

• pandas-拼接函数-append&concat

df = pd.concat([s1,s2,s3] , axis=1)

3. Change the name of the columns to bedrs, bathrs, price_sqr_meter

这是要修改列名

我是直接修改了columns

df.columns=['bedrs' , 'bathrs' , 'price_sqr_meter']

这个可能不友好，所以，原作者使用的是另一个函数来修改，学习下

df.rename(columns = {0: 'bedrs', 1: 'bathrs', 2: 'price_sqr_meter'}, inplace=True)

这里使用了rename函数，参考：pandas函数-rename

4. Create a one column DataFrame with the values of the 3 Series and assign it to 'bigcolumn'

bigcolumn = pd.concat([s1 , s2 , s3])
df2 = pd.DataFrame(bigcolumn)

这里series拼接之后，还是个series，我们转成DataFrame就好了

5. Oops, it seems it is going only until index 99. Is it true?

差点儿忽略了这个问题，拼接之后，我们没有对index做设置，所以默认都是原来的index
所以呢

这里，我们重置下索引就好了

df2.reset_index(drop=True , inplace=True)