我怎样才能创建一个函数 Python

Question

我想在现有代码中添加一段代码，检查 High 列值是否大于列 Open, Low, Close 的行的其他值。我还想检查一下 Low 列的行值是否低于其他列 Open, High, Close 列的行值。因此，在 High 列的值的第 1 行不符合此条件，因为 Open and Close 值高于它，因此它在预期输出中。所以基本上这段代码应该检查每个 High 值是否仍然是最大值并且 Low 值是每一行的最低值。

代码：

import pandas as pd
import numpy as np
import time
import datetime

A =[[1645661520000, 37352.0, 37276.5, 37252.0, 37376.0, 15.56119087], 
[1645661580000, 37376.0, 37414.0, 37376.0, 37314.0, 49.38248589], 
[1645661640000, 37414.0, 37414.0, 37350.0, 37350.0, 45.70306699], 
[1645661700000, 37350.0, 37374.0, 37350.0, 37373.5, 14.4306948], 
[1645661760000, 37373.5, 36588.0, 37373.5, 37388.0, 3.59340947], 
[1645661820000, 37388.0, 37388.0, 37388.0, 39388.0, 21.45525727]]

column_names = ["Unix","Open", "High","Low", "Close", "Volume"]
df = pd.DataFrame(A, columns=column_names)
df.insert(1,"Date", pd.to_datetime(df["Unix"].to_numpy()/1000,unit='s'))
display(df)

预期输出：

Rows: 1, 5, 6
#Row 1 is low column is the highest of all than all the other rows 
#Row 5 the High column is lower than the other columns 
#Row 6 the low column  is higher than the other columns

Answer 1

试试这个：

# columns of interest
val_cols = ['Open', 'High', 'Low',  'Close']

# This is where High condition is violated
high_cond_violated = df['High'] < df[val_cols].max(axis=1)

# This is where Low condition is violated
low_cond_violated = df['Low'] > df[val_cols].min(axis=1)

# These are the indices where either condition is violated
(df.index[high_cond_violated | low_cond_violated] + 1).values.tolist()

输出：

[1, 2, 5, 6]

你可以分别调用，看看到底是哪一个违规了eg

# Only High condition violated
(df.index[high_cond_violated] + 1).values.tolist()
...

我怎样才能创建一个函数 Python

How would I be able to create a function Python

format

numpy

dataframe

python-3.x

pandas