JSON Question
Extracting infromation from multiple JSON files to single CSV file in python
I have a JSON file with multiple dictionaries:
{"team1participants":
[ {
"stats": {
"item1": 3153,
"totalScore": 0,
...
}
},
{
"stats": {
"item1": 2123,
"totalScore": 5,
...
}
},
{
"stats": {
"item1": 1253,
"totalScore": 1,
...
}
}
],
"team2participants":
[ {
"stats": {
"item1": 1853,
"totalScore": 2,
...
}
},
{
"stats": {
"item1": 21523,
"totalScore": 5,
...
}
},
{
"stats": {
"item1": 12503,
"totalScore": 1,
...
}
}
]
}
In other words, the JSON has multiple keys. Each key has a list containing statistics of individual participants.
I have many such JSON files, and I want to extract it to a single CSV file. I can of course do this manually, but this is very tedious. I know of DictWriter, but it seems to work only for single dictionaries. I also know that dictionaries can be concatenated, but it will be problematic because all dictionaries have the same keys.
How can I efficiently extract this to a CSV file?
Answer Source
You can make your data tidy so that each row is a unique observation.
teams = []
items = []
scores = []
for team in d:
for item in d[team]:
teams.append(team)
items.append(item['stats']['item1'])
scores.append(item['stats']['totalScore'])
# Using Pandas.
import pandas as pd
df = pd.DataFrame({'team': teams, 'item': items, 'score': scores})
>>> df
item score team
0 1853 2 team2participants
1 21523 5 team2participants
2 12503 1 team2participants
3 3153 0 team1participants
4 2123 5 team1participants
5 1253 1 team1participants
You could also use a list comprehension instead of a loop.
results = [[team, item['stats']['item1'], item['stats']['totalScore']]
for team in d for item in d[team]]
df = pd.DataFrame(results, columns=['team', 'item', 'score'])
You can then do a pivot table, for example:
>>> df.pivot_table(values='score ', index='team ', columns='item', aggfunc='sum').fillna(0)
item 1253 1853 2123 3153 12503 21523
team
team1participants 1 0 5 0 0 0
team2participants 0 2 0 0 1 5
Also, now that it is a dataframe, it is easy to save it as a CSV.
df.to_csv(my_file_name.csv)