Lesson 4 –新增/刪除列-索引操作

在這節課中我們將回到基礎。我們將使用一個小的資料集，這樣您就可以很容易地理解我要解釋的內容。我們將新增列、刪除列，並以許多不同的方式分割資料。享受吧!

import pandas as pd

# Our small data set
d = [0,1,2,3,4,5,6,7,8,9]

# Create dataframe
df = pd.DataFrame(d)
df

# Lets change the name of the column
df.columns = ['Rev']
df

# Lets add a column
 

df['NewCol'] = 5
df

# Lets modify our new column
df['NewCol'] = df['NewCol'] + 1
df

# We can delete columns
del df['NewCol']
df

# Lets add a couple of columns
df['test'] = 3
df['col'] = df['Rev']
df

# If we wanted, we could change the name of the index
i = ['a','b','c','d','e','f'
 
,'g','h','i','j']
df.index = i
df

現在我們可以開始使用loc選擇dataframe的片段。

df.loc['a']

# df.loc[inclusive:inclusive]
df.loc['a':'d']

我們還可以選擇使用列名

df['Rev']

df[['Rev', 'test']]

df.loc[df.index[0:3],'Rev']

Lessons 5 Stack/Unstack/轉置函式

# Our small data set
d = {'one':[1,1],'two':[2,2]}
i = ['a'
 
,'b']

# Create dataframe
df = pd.DataFrame(data = d, index = i)
df

df.index

stack = df.stack()
stack

# The index now includes the column names
stack.index

unstack = df.unstack()
unstack

(列索引變成行索引，層次不一樣。)

我們還可以使用T(轉置)函式來使用索引來翻轉列名

transpose = df.T
transpose

transpose.index