[英]Convert Json to CSV using Python
Below, is the json structure I am pulling from my online weather station. 下面是我从在线气象站提取的json结构。 I am also including a json_to_csv python script that is supposed to convert json data to csv output, but only returns a "Key" error.
我还包括一个json_to_csv python脚本,该脚本应该将json数据转换为csv输出,但仅返回“ Key”错误。 I want to pull data from "current_observation": only.
我只想从“ current_observation”中提取数据。
{
"response": {
"features": {
"conditions": 1
}
}
, "current_observation": {
"display_location": {
"latitude":"40.466442",
"longitude":"-85.362709",
"elevation":"280.4"
},
"observation_time_rfc822":"Fri, 26 Jan 2018 09:40:16 -0500",
"local_time_rfc822":"Sun, 28 Jan 2018 11:22:47 -0500",
"local_epoch":"1517156567",
"local_tz_short":"EST",
"weather":"Clear",
"temperature_string":"44.6 F (7.0 C)",
}
}
import csv, json, sys
inputFile = open("pywu.cache.json", 'r') #open json file
outputFile = open("CurrentObs.csv", 'w') #load csv file
data = json.load(inputFile) #load json content
inputFile.close() #close the input file
output = csv.writer(outputFile) #create a csv.write
output.writerow(data[0].keys())
for row in data:
output = csv.writer(outputFile) #create a csv.write
output.writerow(data[0].keys())
for row in data:
output.writerow(row.values()) #values row
What's the best method to retrieve the temperature string and convert to .csv format? 检索温度字符串并将其转换为.csv格式的最佳方法是什么? Thank you!
谢谢!
import pandas as pd
df = pd.read_json("pywu.cache.json")
df = df.loc[["local_time_rfc822", "weather", "temperature_string"],"current_observation"].T
df.to_csv("pywu.cache.csv")
maybe pandas can be of help for you. 也许熊猫可以为您提供帮助。 the .read_json() function creates a nice dataframe, from which you can easily choose the desired rows and columns.
.read_json()函数创建一个不错的数据框,您可以从中轻松选择所需的行和列。 and it can save as csv as well.
它也可以另存为csv。
to add latitude and longitude to the csv-line, you can do this: 要将纬度和经度添加到csv行中,您可以执行以下操作:
df = pd.read_json("pywu.cache.csv")
df = df.loc[["local_time_rfc822", "weather", "temperature_string", "display_location"],"current_observation"].T
df = df.append(pd.Series([df["display_location"]["latitude"], df["display_location"]["longitude"]], index=["latitude", "longitude"]))
df = df.drop("display_location")
df.to_csv("pywu.cache.csv")
to print the location in numeric values, you can do this: 要以数字值打印位置,可以执行以下操作:
df = pd.to_numeric(df, errors="ignore")
print(df['latitude'], df['longitude'])
This will find all keys (eg "temperature_string") specified inside of the json blob and then write them to a csv file. 这将找到在json blob内部指定的所有键(例如“ temperature_string”),然后将其写入csv文件。 You can modify this code to get multiple keys.
您可以修改此代码以获取多个密钥。
import csv, json, sys
def find_deep_value(d, key):
# Find a the value of keys hidden within a dict[dict[...]]
# Modified from https://stackoverflow.com/questions/9807634/find-all-occurrences-of-a-key-in-nested-python-dictionaries-and-lists
# @param d dictionary to search through
# @param key to find
if key in d:
yield d[key]
for k in d.keys():
if isinstance(d[k], dict):
for j in find_deep_value(d[k], key):
yield j
inputFile = open("pywu.cache.json", 'r') # open json file
outputFile = open("mypws.csv", 'w') # load csv file
data = json.load(inputFile) # load json content
inputFile.close() # close the input file
output = csv.writer(outputFile) # create a csv.write
# Gives you a list of temperature_strings from within the json
temps = list(find_deep_value(data, "temperature_string"))
output.writerow(temps)
outputFile.close()
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