python pandas 增加一列_Python之pandas新增列
1.导入模块
>>> import pandas as pd
2.解决DataFrame中的行列显示不全问题
>>> pd.set_option('display.max_rows', 100,'display.max_columns', 1000,"display.max_colwidth",1000,'display.width',1000)
3.导入数据表格
>>> air_quality = pd.read_csv(r"C:\Users\Administrator\Desktop\air_quality_no2.csv", index_col=0, parse_dates=True)
>>> air_quality.head()
station_antwerp station_paris station_london
datetime
2019-05-07 02:00:00 NaN NaN 23.0
2019-05-07 03:00:00 50.5 25.0 19.0
2019-05-07 04:00:00 45.0 27.7 19.0
2019-05-07 05:00:00 NaN 50.4 16.0
2019-05-07 06:00:00 NaN 61.9 NaN
4.两列相除得到新列，添加列"ratio_paris_antwerp"，
>>> air_quality["ratio_paris_antwerp"] = air_quality["station_paris"] / air_quality["station_antwerp"]
>>> air_quality.head()
station_antwerp station_paris station_london ratio_paris_antwerp
datetime
2019-05-07 02:00:00 NaN NaN 23.0 NaN
2019-05-07 03:00:00 50.5 25.0 19.0 0.495050
2019-05-07 04:00:00 45.0 27.7 19.0 0.615556
2019-05-07 05:00:00 NaN 50.4 16.0 NaN
2019-05-07 06:00:00 NaN 61.9 NaN NaN
5.单列结果乘指定值，添加列"london_mg_per_cubic"
>>> air_quality["london_mg_per_cubic"] = air_quality["station_london"] * 1.882
>>> air_quality.head()
station_antwerp station_paris station_london ratio_paris_antwerp london_mg_per_cubic
datetime
2019-05-07 02:00:00 NaN NaN 23.0 NaN 43.286
2019-05-07 03:00:00 50.5 25.0 19.0 0.495050 35.758
2019-05-07 04:00:00 45.0 27.7 19.0 0.615556 35.758
2019-05-07 05:00:00 NaN 50.4 16.0 NaN 30.112
2019-05-07 06:00:00 NaN 61.9 NaN NaN NaN
DataFrame中的元素支持数学运算符(+，-，*，/)或逻辑运算符(，=，…)也在元素上起作用，和使用条件表达式过滤表的行。
6.直接新增一列
>>> air_quality["last_colum"] = "NaN"
>>> air_quality.head()
station_antwerp station_paris station_london ratio_paris_antwerp london_mg_per_cubic last_colum
datetime
2019-05-07 02:00:00 NaN NaN 23.0 NaN 43.286 NaN
2019-05-07 03:00:00 50.5 25.0 19.0 0.495050 35.758 NaN
2019-05-07 04:00:00 45.0 27.7 19.0 0.615556 35.758 NaN
2019-05-07 05:00:00 NaN 50.4 16.0 NaN 30.112 NaN
2019-05-07 06:00:00 NaN 61.9 NaN NaN NaN NaN
7.修改指定列的名称
>>> air_quality_renamed = air_quality.rename(
columns={"station_antwerp": "BETR801",
"station_paris": "FR04014",
"station_london": "London Westminster"})
... ... ... >>> air_quality_renamed.head()
BETR801 FR04014 London Westminster ratio_paris_antwerp london_mg_per_cubic
datetime
2019-05-07 02:00:00 NaN NaN 23.0 NaN 43.286
2019-05-07 03:00:00 50.5 25.0 19.0 0.495050 35.758
2019-05-07 04:00:00 45.0 27.7 19.0 0.615556 35.758
2019-05-07 05:00:00 NaN 50.4 16.0 NaN 30.112
2019-05-07 06:00:00 NaN 61.9 NaN NaN NaN
8.使用函数将列名转换为小写字母
>>> air_quality_renamed = air_quality_renamed.rename(columns=str.lower)
>>> air_quality_renamed.head()
betr801 fr04014 london westminster ratio_paris_antwerp london_mg_per_cubic
datetime
2019-05-07 02:00:00 NaN NaN 23.0 NaN 43.286
2019-05-07 03:00:00 50.5 25.0 19.0 0.495050 35.758
2019-05-07 04:00:00 45.0 27.7 19.0 0.615556 35.758
2019-05-07 05:00:00 NaN 50.4 16.0 NaN 30.112
2019-05-07 06:00:00 NaN 61.9 NaN NaN NaN
rename()功能可用于行标签和列标签,提供一个字典，其中包含键，当前名称和值，以及新名称，以更新相应的名称，还可以是使用函数。