Python nested Dictionaries to csv-CodePudding

I have a data set in this format:

data = { 'sensor1': {'units': 'x', 'values': [{'time': 17:00, 'value': 10},
                                              {'time': 17:10, 'value': 12}, 
                                              {'time': 17:20, 'value' :7}, ...]}
         'sensor2': {'units': 'x', 'values': [{'time': 17:00, 'value': 9},
                                              {'time': 17:20, 'value': 11}, ...]}
        }

And I want to collect the data to put into a csv like:

time, sensor1, sensor2
17:00, 10, 9,
17:10, 12, ,
17:20, 7, 11,
...

I need to use the csv module so I require a list of dictionaries like so:

[{'time': 17:00, 'sensor1': 10, 'sensor2': 9}, ... ]

I know that

fields = list(data.keys())

Will go into csv write as the header. It's just the rows I can't format properly. Especially since the times don't always exist in both sensors. e.g. 17:10 has a value in sensor 1 but does not exist in sensor 2.

CodePudding user response：

You can use pandas to create a dataframe from your data and save it as CSV:

import pandas as pd

data = {
    "sensor1": {
        "units": "x",
        "values": [
            {"time": "17:00", "value": "10"},
            {"time": "17:10", "value": "12"},
            {"time": "17:20", "value": "7"},
        ],
    },
    "sensor2": {
        "units": "x",
        "values": [
            {"time": "17:00", "value": "9"},
            {"time": "17:20", "value": "11"},
        ],
    },
}

df = pd.DataFrame(
    [
        {"time": vv["time"], "column": k, "value": vv["value"]}
        for k, v in data.items()
        for vv in v["values"]
    ],
)
df = df.pivot(index="time", columns="column", values="value").reset_index()

df.to_csv("data.csv", index=False)

saves data.csv:

time,sensor1,sensor2
17:00,10,9
17:10,12,
17:20,7,11

CodePudding user response：

You can do it in 2 steps.

data = { 'sensor1': {'units': 'x', 'values': [{'time': '17:00', 'value': 10},
                                              {'time': '17:10', 'value': 12}, 
                                              {'time': '17:20', 'value' :7},
                                             ]},
         'sensor2': {'units': 'x', 'values': [{'time': '17:00', 'value': 9},
                                              {'time': '17:20', 'value': 11},
                                             ]},
        }

# first step: dictionary keyed by time {time:t,{'sensorx':v,}}
dic = {}
for sensor in data:
    for sample in data[sensor]['values']:
        if not dic.get( sample['time']):
            dic[ sample['time']] = {} # create the record
        dic[ sample[ 'time']][sensor] = sample['value']

# second step: generate CSV
columns=['time', 'sensor1', 'sensor2']
import csv
f = open( 'zz.csv', 'w', newline='')
writer = csv.DictWriter( f, columns)
writer.writeheader()
for key in dic:
    writer.writerow( dict( [('time',key)]   list( dic[key].items())))

The result will be:

    time,sensor1,sensor2
    17:00,10,9
    17:10,12,
    17:20,7,11