最近经常看到各平台里都有Python的广告,都是对excel的操作,这里明哥收集整理了一下pandas对excel的操作方法和使用过程。本篇介绍 pandas 的 DataFrame
对列 (Column) 的处理方法。示例数据请通过明哥的gitee进行下载。
增加计算列
pandas 的 DataFrame
,每一行或每一列都是一个序列 (Series
)。比如:
import pandas as pd df1 = pd.read_excel('./excel-comp-data.xlsx');
此时,用 type(df1['city']
,显示该数据列(column)的类型是 pandas.core.series.Series
。理解每一列都是 Series
非常重要,因为 pandas 基于 numpy,对数据的计算都是整体计算。深刻理解这个,才能理解后面要说的诸如 apply()
函数等。
如果列名 (column name)没有空格,则列有两种方式表达:
df1['city'] df1.city
如果列名有空格,或者创建新列(即该列不存在,需要创建,第一次使用的变量),则只能用第一种表达式。
假设我们要对三个月的数据进行汇总,可以使用下面的方法。实际上就是创建一个新的数据列:
# 由于是创建,不能使用 df.Total df1['Total'] = df1['Jan'] + df1['Feb'] + df1['Mar']
df1['Jan']
到 df1['Mar']
都是 Series
,所以使用 +
号,可以得到三个 Series
对应位置的数据合计。
当然,也可以用下面的方式:
df1['total'] = df1.Jan + df1.Feb + df1.Mar
增加条件计算列
假设现在要根据合计数 (Total 列),当 Total 大于 200,000 ,类别为 A,否则为 B。在 Excel 中实现用的是 IF
函数,但在 pandas 中需要用到 numpy 的 where
函数:
df1['category'] = np.where(df1['total'] > 200000, 'A', 'B')
在指定位置插入列
上面方法增加的列,位置都是放在最后。如果想要在指定位置插入列,要用 dataframe.insert()
方法。假设我们要在 state
列后面插入一列,这一列是 state
的简称 (abbreviation)。在 Excel 中,根据 state 来找到 state 的简称 ,一般用 VLOOKUP
函数。我们用两种方法来实现,第一种方法,简称来自 Python 的 dict。
数据来源:
state_to_code = {"VERMONT": "VT", "GEORGIA": "GA", "IOWA": "IA", "Armed Forces Pacific": "AP", "GUAM": "GU", "KANSAS": "KS", "FLORIDA": "FL", "AMERICAN SAMOA": "AS", "NORTH CAROLINA": "NC", "HAWAII": "HI", "NEW YORK": "NY", "CALIFORNIA": "CA", "ALABAMA": "AL", "IDAHO": "ID", "FEDERATED STATES OF MICRONESIA": "FM", "Armed Forces Americas": "AA", "DELAWARE": "DE", "ALASKA": "AK", "ILLINOIS": "IL", "Armed Forces Africa": "AE", "SOUTH DAKOTA": "SD", "CONNECTICUT": "CT", "MONTANA": "MT", "MASSACHUSETTS": "MA", "PUERTO RICO": "PR", "Armed Forces Canada": "AE", "NEW HAMPSHIRE": "NH", "MARYLAND": "MD", "NEW MEXICO": "NM", "MISSISSIPPI": "MS", "TENNESSEE": "TN", "PALAU": "PW", "COLORADO": "CO", "Armed Forces Middle East": "AE", "NEW JERSEY": "NJ", "UTAH": "UT", "MICHIGAN": "MI", "WEST VIRGINIA": "WV", "WASHINGTON": "WA", "MINNESOTA": "MN", "OREGON": "OR", "VIRGINIA": "VA", "VIRGIN ISLANDS": "VI", "MARSHALL ISLANDS": "MH", "WYOMING": "WY", "OHIO": "OH", "SOUTH CAROLINA": "SC", "INDIANA": "IN", "NEVADA": "NV", "LOUISIANA": "LA", "NORTHERN MARIANA ISLANDS": "MP", "NEBRASKA": "NE", "ARIZONA": "AZ",<em>本文来源gao.dai.ma.com搞@代*码(网$</em> "WISCONSIN": "WI", "NORTH DAKOTA": "ND", "Armed Forces Europe": "AE", "PENNSYLVANIA": "PA", "OKLAHOMA": "OK", "KENTUCKY": "KY", "RHODE ISLAND": "RI", "DISTRICT OF COLUMBIA": "DC", "ARKANSAS": "AR", "MISSOURI": "MO", "TEXAS": "TX", "MAINE": "ME"}