パンダを使ってwundergoundの気象データを掻き集める

Question

シェーン・リンでは、 Analysis of Weather dataの非常に便利なスクリプトを見つけました。キャンペーン応募はこちらからデータをこすりために使用される最初のスクリプトは、次のようにされています。しかし、私はエラーを取得する

import requests 
import pandas as pd 
from dateutil import parser, rrule 
from datetime import datetime, time, date 
import time 

def getRainfallData(station, day, month, year): 
    """ 
    Function to return a data frame of minute-level weather data for a single Wunderground PWS station. 

    Args: 
     station (string): Station code from the Wunderground website 
     day (int): Day of month for which data is requested 
     month (int): Month for which data is requested 
     year (int): Year for which data is requested 

    Returns: 
     Pandas Dataframe with weather data for specified station and date. 
    """ 
    url = "http://www.wunderground.com/weatherstation/WXDailyHistory.asp?ID={station}&day={day}&month={month}&year={year}&graphspan=day&format=1" 
    full_url = url.format(station=station, day=day, month=month, year=year) 
    # Request data from wunderground data 
    response = requests.get(full_url, headers={'User-agent': 'Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2228.0 Safari/537.36'}) 
    data = response.text 
    # remove the excess <br> from the text data 
    data = data.replace('<br>', '') 
    # Convert to pandas dataframe (fails if issues with weather station) 
    try: 
     dataframe = pd.read_csv(io.StringIO(data), index_col=False) 
     dataframe['station'] = station 
    except Exception as e: 
     print("Issue with date: {}-{}-{} for station {}".format(day,month,year, station)) 
     return None 
    return dataframe 

# Generate a list of all of the dates we want data for 
start_date = "2016-08-01" 
end_date = "2016-08-31" 
start = parser.parse(start_date) 
end = parser.parse(end_date) 
dates = list(rrule.rrule(rrule.DAILY, dtstart=start, until=end)) 

# Create a list of stations here to download data for 
stations = ["ILONDON28"] 
# Set a backoff time in seconds if a request fails 
backoff_time = 10 
data = {} 

# Gather data for each station in turn and save to CSV. 
for station in stations: 
    print("Working on {}".format(station)) 
    data[station] = [] 
    for date in dates: 
     # Print period status update messages 
     if date.day % 10 == 0: 
      print("Working on date: {} for station {}".format(date, station)) 
     done = False 
     while done == False: 
      try: 
       weather_data = getRainfallData(station, date.day, date.month, date.year) 
       done = True 
      except ConnectionError as e: 
       # May get rate limited by Wunderground.com, backoff if so. 
       print("Got connection error on {}".format(date)) 
       print("Will retry in {} seconds".format(backoff_time)) 
       time.sleep(10) 
     # Add each processed date to the overall data 
     data[station].append(weather_data) 
    # Finally combine all of the individual days and output to CSV for analysis. 
    pd.concat(data[station]).to_csv("data/{}_weather.csv".format(station)) 

：

Working on ILONDONL28 
Issue with date: 1-8-2016 for station ILONDONL28 
Issue with date: 2-8-2016 for station ILONDONL28 
Issue with date: 3-8-2016 for station ILONDONL28 
Issue with date: 4-8-2016 for station ILONDONL28 
Issue with date: 5-8-2016 for station ILONDONL28 
Issue with date: 6-8-2016 for station ILONDONL28 

誰もがこのエラーで私を助けることができますか？

このlinkに示すように、選択したステーションのデータと期間が利用可能です。

Answer 1

出力は例外が発生しているためです。 print eを追加した場合、これはimport ioがスクリプトの先頭にないためです。第二に、あなたが与えた駅名は1人のキャラクターによって出ていた。次のことを試してみてください。

次のように始まるあなたに出力したCSVファイルを与える

import io 
import requests 
import pandas as pd 
from dateutil import parser, rrule 
from datetime import datetime, time, date 
import time 

def getRainfallData(station, day, month, year): 
    """ 
    Function to return a data frame of minute-level weather data for a single Wunderground PWS station. 

    Args: 
     station (string): Station code from the Wunderground website 
     day (int): Day of month for which data is requested 
     month (int): Month for which data is requested 
     year (int): Year for which data is requested 

    Returns: 
     Pandas Dataframe with weather data for specified station and date. 
    """ 

    url = "http://www.wunderground.com/weatherstation/WXDailyHistory.asp?ID={station}&day={day}&month={month}&year={year}&graphspan=day&format=1" 
    full_url = url.format(station=station, day=day, month=month, year=year) 

    # Request data from wunderground data 
    response = requests.get(full_url) 
    data = response.text 
    # remove the excess <br> from the text data 
    data = data.replace('<br>', '') 

    # Convert to pandas dataframe (fails if issues with weather station) 
    try: 
     dataframe = pd.read_csv(io.StringIO(data), index_col=False) 
     dataframe['station'] = station 
    except Exception as e: 
     print("Issue with date: {}-{}-{} for station {}".format(day,month,year, station)) 
     return None 

    return dataframe 

# Generate a list of all of the dates we want data for 
start_date = "2016-08-01" 
end_date = "2016-08-31" 
start = parser.parse(start_date) 
end = parser.parse(end_date) 
dates = list(rrule.rrule(rrule.DAILY, dtstart=start, until=end)) 

# Create a list of stations here to download data for 
stations = ["ILONDONL28"] 
# Set a backoff time in seconds if a request fails 
backoff_time = 10 
data = {} 

# Gather data for each station in turn and save to CSV. 
for station in stations: 
    print("Working on {}".format(station)) 
    data[station] = [] 
    for date in dates: 
     # Print period status update messages 
     if date.day % 10 == 0: 
      print("Working on date: {} for station {}".format(date, station)) 
     done = False 
     while done == False: 
      try: 
       weather_data = getRainfallData(station, date.day, date.month, date.year) 
       done = True 
      except ConnectionError as e: 
       # May get rate limited by Wunderground.com, backoff if so. 
       print("Got connection error on {}".format(date)) 
       print("Will retry in {} seconds".format(backoff_time)) 
       time.sleep(10) 
     # Add each processed date to the overall data 
     data[station].append(weather_data) 
    # Finally combine all of the individual days and output to CSV for analysis. 
    pd.concat(data[station]).to_csv(r"data/{}_weather.csv".format(station)) 

：

,Time,TemperatureC,DewpointC,PressurehPa,WindDirection,WindDirectionDegrees,WindSpeedKMH,WindSpeedGustKMH,Humidity,HourlyPrecipMM,Conditions,Clouds,dailyrainMM,SoftwareType,DateUTC,station 
0,2016-08-01 00:05:00,17.8,11.6,1017.5,ESE,120,0.0,0.0,67,0.0,,,0.0,WeatherCatV2.31B93,2016-07-31 23:05:00,ILONDONL28 
1,2016-08-01 00:20:00,17.7,11.0,1017.5,SE,141,0.0,0.0,65,0.0,,,0.0,WeatherCatV2.31B93,2016-07-31 23:20:00,ILONDONL28 
2,2016-08-01 00:35:00,17.5,10.8,1017.5,South,174,0.0,0.0,65,0.0,,,0.0,WeatherCatV2.31B93,2016-07-31 23:35:00,ILONDONL28 

CSVファイルを取得していない場合、私はあなたが出力ファイル名のフルパスを追加提案します。