pandas 打印在带有 f 字符串的列中找到的最大值

Question

如果我有一些虚构的数据...如何只打印在名为 Temperature 的列中找到的最大值的索引（日期和时间戳）？

import numpy as np
import pandas as pd
np.random.seed(11)

rows,cols = 50000,2
data = np.random.rand(rows,cols) 
tidx = pd.date_range('2019-01-01', periods=rows, freq='H') 
df = pd.DataFrame(data, columns=['Temperature','Value'], index=tidx)

maxy = df.Temperature.max()
maxDate = df.loc[df['Temperature'].idxmax()]

如果我打印 maxDate 会有很多不需要的信息..

print(maxy)
print(maxDate)

这输出：

0.9999949674183947
Temperature    0.999995
Value          0.518413
Name: 2023-01-06 02:00:00, dtype: float64

最终我希望创建一个只打印 maximum temperature recorded in the dataset is 0.999995 found on 2023-01-06 02:00:00 的 f 字符串，而不需要额外的信息，例如 Name: 和 , dtype: float64 以及 Value 0.518413 专栏...感谢任何提示和技巧

Answer 1

你的 f 字符串可能是：

f'maximum temperature recoded in the dataset is {maxy} found on {maxDate.name}'

或没有maxy:

f'maximum temperature recoded in the dataset is {maxDate.Temperature} found on {maxDate.name}'

输出：

'maximum temperature recoded in the dataset is 0.9999949674183947 found on 2023-01-06 02:00:00'

Answer 2

最高温度的条目可以超过 1 个。

maxy = df.Temperature.max()
max_dates = df[df['Temperature'] == maxy].index.astype(str).to_list()
print(f'Max temperature recorded in dataset is {maxy} on {",".join(max_dates)}')

输出：

Max temperature recorded in dataset is 0.9999949674183947 on 2023-01-06 02:00:00

pandas 打印在带有 f 字符串的列中找到的最大值

pandas printing maximum value found in a column with an f string

python

string-formatting

pandas