Question

尝试对时间序列数据和iterrows执行操作。我已经能够构建一个在日期添加值但不使用pandas的函数。另外，我不知道如何使用乘法，减法，除法等来做到这一点。

from operator import *
import pandas as pd
import requests

prices_url = r'https://gist.githubusercontent.com/ryan413/596811e3cd15ad891f7cb3cf8ab7c78b/raw/af359e13b26af7699a2afedc9b148dbb19df25b3/prices.csv'

r = requests.get(prices_url)

with open("prices.csv", 'w', encoding='utf-8') as f:
    f.write(r.text)

df = pd.read_csv('prices.csv',index_col=0, header=0)

# df.columns = Index(['EUR', 'CAD', 'NOK', 'SPY', 'EUR.1'], dtype='object')

#                  EUR       CAD        NOK        SPY      EUR.1
# 2/7/2017   31.234616  5.117412  72.662151  93.685559  73.176038
# 2/8/2017   31.428942  5.471865  72.547450  93.860313  73.889394
# 2/9/2017   30.871875  4.984493  73.030060  94.652531  72.944198
# 2/10/2017  30.716414  4.918033  73.614387  95.182618  75.887682
# 2/13/2017  30.133437  5.305716  74.164088  95.916584  76.568937


def add_rows(df_prices):
    row_sum = {}
    for idx, col in df_prices.iterrows():
        row_sum[idx] = sum(col)
    return row_sum

sum_of_rows = add_rows(df)

for k,v in sum_of_rows.items():
    print(k," - ", v)

# 2/7/2017  -  275.875777014
# 2/8/2017  -  277.197963968
# 2/9/2017  -  276.483156429
# 2/10/2017  -  280.319134197
# 2/13/2017  -  282.088761272
# 2/14/2017  -  280.555245767
# 2/15/2017  -  281.487035784
# 2/16/2017  -  281.282552346
# 2/17/2017  -  280.508299074

# values in each row are added together

Q1：使用pandas有更简单的方法吗？

def multiplication(df_prices):
    row_multiply = {}
    for idx, col in df_prices.iterrows():
        row_multiply[idx] = mul(col,col)
    return row_multiply

mult_of_rows = multiplication(df)

for k, v in mult_of_rows.items():
    print(k, " - ", mul(v, v))

# 
# 3/3/2017  -  EUR       926.858939
# CAD         7.304602
# NOK      5603.190074
# SPY      9842.184083
# EUR.1    5915.492570
# Name: 3/3/2017, dtype: float64
# trying to multiply each of the the values with each other

# EUR * CAD * NOK * SPY = value I'm trying to get for each of the rows

Q2：我如何通过乘法做同样的事情？师？减法？

Answer 1

你去：

sum cols:

df.sum(axis=1)

multiply:

import numpy as np
df.apply(lambda row: np.prod(row), axis=1)

如果您想对列进行求和（这样会更有意义），您只需将axis从1更改为0。

也可以乘以/表示常数：

df['Eurocents'] = df.EUR * 100

或整个dataframeL

df_in_cents = df * 100

我希望这就是你要找的东西。

python pandas iterrow sum乘法除法

1 个答案: