Convert Json to CSV using Python

Question

Below, is the json structure I am pulling from my online weather station. 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. I want to pull data from "current_observation": only.

{
  "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? Thank you!

Your code is not properly indented; please fix it so we can run it. — Adam Barnes
– Adam Barnes, Commented Feb 1, 2018 at 17:38
So the output you want is a CSV file with rows of just a single column, each showing only temperature_string? — NFB
– NFB, Commented Feb 1, 2018 at 17:40
I would like to have local_time, weather and temperature_string, if possible. — user5834454
– user5834454, Commented Feb 1, 2018 at 17:52

habet · Accepted Answer · 2018-02-06 17:15:45Z

2

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. the .read_json() function creates a nice dataframe, from which you can easily choose the desired rows and columns. and it can save as csv as well.

to add latitude and longitude to the csv-line, you can do this:

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:

df = pd.to_numeric(df, errors="ignore")
print(df['latitude'], df['longitude'])

edited Feb 6, 2018 at 17:15

answered Feb 3, 2018 at 10:08

habet

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16 Comments

user5834454 Over a year ago

How would you go about parsing latitude/ longitude using pandas and writing a single row output in CSV format?

habet Over a year ago

not sure, what you mean with parsing exactly. adding latitutude and longitude can be done like this for example (i will add it to the answer)

user5834454 Over a year ago

Thanks for amending the code. By parsing, I mean extracting both latitude and longitude from the string "display_location". Not sure if it's possible to just display the numerical value for each?

habet Over a year ago

sure, you can convert the resulting pd.Series() object with pd.to_numeric to a numeric values. with errors="ignore" you skip the non-numeric values. Then you can index the object just like a dict. (see code in answer). and sorry for all the editing.

user5834454 Over a year ago

NP with all the edits - it helps better understand were code is placed, within pandas. With your most recent additions, do I add pd.to_numeric directly after the pd.Series and before df.drop?

|

Ross · Accepted Answer · 2018-02-01 18:06:18Z

1

This will find all keys (e.g. "temperature_string") specified inside of the json blob and then write them to a csv file. You can modify this code to get multiple keys.

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()

answered Feb 1, 2018 at 18:06

Ross

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1 Comment

user5834454 Over a year ago

PERFECT - Thank you!

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