Question

我想找出满足条件RSI < 25的行。但是，结果是用一个数据帧生成的。是否可以为任何一行创建单独的数据框？

谢谢。

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from pandas_datareader import data as wb

stock='TSLA'

ck_df = wb.DataReader(stock,data_source='yahoo',start='2015-01-01')

rsi_period = 14

chg = ck_df['Close'].diff(1)

gain = chg.mask(chg<0,0)
ck_df['Gain'] = gain

loss = chg.mask(chg>0,0)
ck_df['Loss'] = loss

avg_gain = gain.ewm(com = rsi_period-1,min_periods=rsi_period).mean()
avg_loss = loss.ewm(com = rsi_period-1,min_periods=rsi_period).mean()

ck_df['Avg Gain'] = avg_gain
ck_df['Avg Loss'] = avg_loss

rs = abs(avg_gain/avg_loss)

rsi = 100-(100/(1+rs))

ck_df['RSI'] = rsi

RSIFactor = ck_df['RSI'] <25

ck_df[RSIFactor]

Answer 1

如果您想知道RSI <25在什么索引上，则只需使用：

ck_df[ck_df['RSI'] <25].index

结果还将是一个数据框。如果您坚持要制作新的，则：

new_df = ck_df[ck_df['RSI'] <25].copy()

Answer 2

要将@Omkar解决方案找到的行拆分为单独的数据帧，可以使用以下功能：Pandas: split dataframe into multiple dataframes by number of rows;

def split_dataframe_to_chunks(df, n):
    df_len = len(df)
    count = 0
    dfs = []

    while True:
        if count > df_len-1:
            break

        start = count
        count += n
        dfs.append(df.iloc[start : count])
    return dfs

由此您将获得数据帧列表。

如何通过排序的数据创建新的数据框

2 个答案: