循环遍历 pandas DataFrame答案

【问题标题】：Looping over pandas DataFrame循环遍历 pandas DataFrame
【发布时间】：2023-03-24 06:29:01
【问题描述】：

我有一个奇怪的问题，即每次迭代的结果都不会改变。代码如下：

import pandas as pd
import numpy as np

X = np.arange(10,100)
Y = X[::-1]
Z = np.array([X,Y]).T

df = pd.DataFrame(Z ,columns = ['col1','col2'])
dif = df['col1'] - df['col2']

for gap in range(100):
    Up = dif > gap
    Down = dif < -gap

    df.loc[Up,'predict'] = 'Up'
    df.loc[Down,'predict'] = 'Down'

    df_result = df.dropna()
    Total = df.shape[0]
    count = df_result.shape[0]
    ratio = count/Total
    print(f'Total: {Total}; count: {count}; ratio: {ratio}')

结果总是

Total: 90; count: 90; ratio: 1.0

什么时候不应该。提前谢谢你

【问题讨论】：

标签： python-3.x pandas loops numpy na

【解决方案1】：

在发布此问题 5 分钟后找到问题的根源。我只需要将 dataFrame 重置为原始数据即可解决问题。

import pandas as pd
import numpy as np

X = np.arange(10,100)
Y = X[::-1]
Z = np.array([X,Y]).T

df = pd.DataFrame(Z ,columns = ['col1','col2'])
df2 = df.copy()#added this line to preserve the original df
dif = df['col1'] - df['col2']

for gap in range(100):
    df = df2.copy()#reset the altered df back to the original
    Up = dif > gap
    Down = dif < -gap

    df.loc[Up,'predict'] = 'Up'
    df.loc[Down,'predict'] = 'Down'

    df_result = df.dropna()
    Total = df.shape[0]
    count = df_result.shape[0]
    ratio = count/Total
    print(f'Total: {Total}; count: {count}; ratio: {ratio}')

【讨论】：