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数据准备

import pandas as pd

df = pd.DataFrame([['ABC'],
                   ['FJZ'],
                   ['FOC']
                  ],columns=['Site'])

df

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在平时开发中，添加新数据列涉及到以下三种常用方法:

1. 直接赋值

语法: df[新列名] = 值

import pandas as pd
import numpy as np

df = pd.DataFrame([['ABC'],
                   ['FJZ'],
                   ['FOC']
                  ],columns=['Site'])

# 添加空值数据列
# 添加'Level','Remark'列,将两列的值设置为空(keep blank)
df['Level'] = np.nan
df['Remark'] = np.nan

2.reindex()函数

语法: df.reindex(columns=[原来所有的列名,新增列名],fill_value=值)

import pandas as pd

df = pd.DataFrame([['ABC'],
                   ['FJZ'],
                   ['FOC']
                  ],columns=['Site'])

# 添加新列'Quantity'和'Product_number',并将其值设置为0
df = df.reindex(columns = ['Site', 'Quantity', 'Product_number'], fill_value=0)

注意: 不加fill_value参数，默认值为nan

3.loc()函数

语法: df.loc[:,新列名] = 值

import pandas as pd

df = pd.DataFrame([['ABC'],
                   ['FJZ'],
                   ['FOC']
                  ],columns=['Site'])

# 添加新列'Description',并将其值设置为'Good'
df.loc[:,'Description'] = 'Good'

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练习案例:增加一个自增id列

import pandas as pd

df = pd.DataFrame([['L123',1,2,3],
                   ['L456',4,5,6],
                   ['L437',7,8,9],
                   ['L112',10,11,12],
                   ['L211',13,14,15],
                   ['L985',16,17,18]
                  ],columns=['Material','W1|6/22','W2|6/23','W3|6/24'])

df.index = df.index + 1
df = df.reset_index()
df = df.rename(columns = {'index':'id'})

df

df(增加自增id列)