如果你有各种各样的对象列,比如74个对象列和2个Int列,其中每个值都有字母表示单位:
import pandas as pd
import numpy as np
dataurl = 'https://raw.githubusercontent.com/RubenGavidia/Pandas_Portfolio.py/main/Wes_Mckinney.py/nutrition.csv'
nutrition = pd.read_csv(dataurl,index_col=[0])
nutrition.head(3)
输出:
name serving_size calories total_fat saturated_fat cholesterol sodium choline folate folic_acid ... fat saturated_fatty_acids monounsaturated_fatty_acids polyunsaturated_fatty_acids fatty_acids_total_trans alcohol ash caffeine theobromine water
0 Cornstarch 100 g 381 0.1g NaN 0 9.00 mg 0.4 mg 0.00 mcg 0.00 mcg ... 0.05 g 0.009 g 0.016 g 0.025 g 0.00 mg 0.0 g 0.09 g 0.00 mg 0.00 mg 8.32 g
1 Nuts, pecans 100 g 691 72g 6.2g 0 0.00 mg 40.5 mg 22.00 mcg 0.00 mcg ... 71.97 g 6.180 g 40.801 g 21.614 g 0.00 mg 0.0 g 1.49 g 0.00 mg 0.00 mg 3.52 g
2 Eggplant, raw 100 g 25 0.2g NaN 0 2.00 mg 6.9 mg 22.00 mcg 0.00 mcg ... 0.18 g 0.034 g 0.016 g 0.076 g 0.00 mg 0.0 g 0.66 g 0.00 mg 0.00 mg 92.30 g
3 rows × 76 columns
nutrition.dtypes
name object
serving_size object
calories int64
total_fat object
saturated_fat object
...
alcohol object
ash object
caffeine object
theobromine object
water object
Length: 76, dtype: object
nutrition.dtypes.value_counts()
object 74
int64 2
dtype: int64
将所有列转换为数值的一个好方法是使用正则表达式来替换单位,并使用astype(float)来更改列数据类型为float:
nutrition.index = pd.RangeIndex(start = 0, stop = 8789, step= 1)
nutrition.set_index('name',inplace = True)
nutrition.replace('[a-zA-Z]','', regex= True, inplace=True)
nutrition=nutrition.astype(float)
nutrition.head(3)
输出:
serving_size calories total_fat saturated_fat cholesterol sodium choline folate folic_acid niacin ... fat saturated_fatty_acids monounsaturated_fatty_acids polyunsaturated_fatty_acids fatty_acids_total_trans alcohol ash caffeine theobromine water
name
Cornstarch 100.0 381.0 0.1 NaN 0.0 9.0 0.4 0.0 0.0 0.000 ... 0.05 0.009 0.016 0.025 0.0 0.0 0.09 0.0 0.0 8.32
Nuts, pecans 100.0 691.0 72.0 6.2 0.0 0.0 40.5 22.0 0.0 1.167 ... 71.97 6.180 40.801 21.614 0.0 0.0 1.49 0.0 0.0 3.52
Eggplant, raw 100.0 25.0 0.2 NaN 0.0 2.0 6.9 22.0 0.0 0.649 ... 0.18 0.034 0.016 0.076 0.0 0.0 0.66 0.0 0.0 92.30
3 rows × 75 columns
nutrition.dtypes
serving_size float64
calories float64
total_fat float64
saturated_fat float64
cholesterol float64
...
alcohol float64
ash float64
caffeine float64
theobromine float64
water float64
Length: 75, dtype: object
nutrition.dtypes.value_counts()
float64 75
dtype: int64
现在数据集是干净的,你只能用regex和astype()对这个数据帧进行数值操作。
如果你想收集单位,并粘贴在标题如胆固醇,你可以使用下面的代码:
nutrition.index = pd.RangeIndex(start = 0, stop = 8789, step= 1)
nutrition.set_index('name',inplace = True)
nutrition.astype(str).replace('[^a-zA-Z]','', regex= True)
units = nutrition.astype(str).replace('[^a-zA-Z]','', regex= True)
units = units.mode()
units = units.replace('', np.nan).dropna(axis=1)
mapper = { k: k + "_" + units[k].at[0] for k in units}
nutrition.rename(columns=mapper, inplace=True)
nutrition.replace('[a-zA-Z]','', regex= True, inplace=True)
nutrition=nutrition.astype(float)