Python通过Jupyter笔记本预测温度

Question

美国国家海洋与大气管理局（NOAA）运营着数千个气候观测站（大部分在美国），这些观测站收集有关当地气候的信息。 除其他事项外，每个站点每天记录的最高和最低温度。 这些数据称为“质量控制的本地气候数据”，可在此处公开获得并在 此处进行描述。

temperatures.csv包含该数据集的摘录。 每行代表一天中一个站点的华氏温度读数。 （温度实际上是当天该站观测到的最高温度。）所有读数均来自2015年和加利福尼亚站。

假设您正在计划今年圣诞节假期前往优胜美地旅行，并且您想预测12月25日的温度。请使用predict_temperature为该天的温度读数计算预测值。

我正在使用Python Jupyter Notebook解决此问题。

import numpy as np
from datascience import *

# These lines do some fancy plotting magic.
import matplotlib
%matplotlib inline
import matplotlib.pyplot as plt
plt.style.use('fivethirtyeight')
import warnings
warnings.simplefilter('ignore', FutureWarning)
PREDICTION_RADIUS = 7

让我们解决这个问题。 我们会将每个日期转换为自年初以来的天数。 在[72]中：

def get_month(date):
    """The month in the year for a given date.

    >>> get_month(315)
    3
    """
    return int(date / 100)
​
def get_day_in_month(date):
    """The day in the month for a given date.

    >>> get_day_in_month(315)
    15
    """
    return date % 100
​
DAYS_IN_MONTHS = Table().with_columns(
    "Month", np.arange(1, 12+1),
    "Days in Month", make_array(31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31))
​
# A table with one row for each month.  For each month, we have
# the number of the month (e.g. 3 for March), the number of
# days in that month in 2015 (e.g. 31 for March), and the
# number of days in the year before the first day of that month
# (e.g. 0 for January or 59 for March).
DAYS_SINCE_YEAR_START = DAYS_IN_MONTHS.with_column(
    "Days since start of year", np.cumsum(DAYS_IN_MONTHS.column("Days in Month")) - DAYS_IN_MONTHS.column("Days in Month"))
​
def days_since_year_start(month):
    """The number of days in the year before this month starts.

    month should be the number of a month, like 3 for March.

    >>> days_since_year_start(3)
    59
    """
    return DAYS_SINCE_YEAR_START.where("Month", are.equal_to(month))\
                                .column("Days since start of year")\
                                .item(0)
​
# First, extract the month and day for each reading.
with_month_and_day = temperatures.with_columns(
    "Month", temperatures.apply(get_month, "Date"),
    "Day in month", temperatures.apply(get_day_in_month, "Date"))
# Compute the days-since-year-start for each month and day.
fixed_dates = with_month_and_day.apply(days_since_year_start, "Month") + with_month_and_day.column("Day in month")
# Add those to the table.
with_dates_fixed = with_month_and_day.with_column("Days since start of year", fixed_dates).drop("Month", "Day in month")
with_dates_fixed

def predict_temperature(day):
    """A prediction of the temperature (in Fahrenheit) on a given day at some station.
    """
    nearby_readings = with_dates_fixed.where("Days since start of year", are.between_or_equal_to(day - PREDICTION_RADIUS, day + PREDICTION_RADIUS))
    return np.average(nearby_readings.column("Temperature"))

我试图解决该错误：

Christmas_prediction = predict_temperature(days_since_year_start(12) + 25) 
Christmas_prediction

但这给了我一个错误。 SyntaxError：语法无效

有什么我想念的吗？

Answer 1

通过在Jupyter Notebook中运行，我能够解决此问题。