I have a dictionary like this:
{'https://github.com/project1': {'Batchfile': '91', 'Gradle': '110', 'INI': '25', 'Java': '1879', 'Markdown': '393', 'QMake': '52', 'Shell': '161', 'Text': '202', 'XML': '943'}}
{'https://github.com/project2': {'Batchfile': '91', 'Gradle': '123', 'INI': '25', 'Java': '1305', 'Markdown': '121', 'QMake': '52', 'Shell': '161', 'XML': '234'}}
{'https://github.com/project3': {'Batchfile': '91', 'Gradle': '360', 'INI': '27', 'Java': '805', 'Markdown': '27', 'QMake': '156', 'Shell': '161', 'XML': '380'}}
It is a structured in this way:
{'url': {'lang1': 'locs', 'lang2': 'locs', ...}}
{'url2': {'lang6': 'locs', 'lang5': 'locs', ...}}
where lang stay for languages and locs stay for line of codes (related to the previous language).
What i want to do is print this dictionary in a pretty way,so i can see the results before the export. After that i want to export the dictionary into a csv file to make other operation. The problem is the languages are not sorted. That is what i mean:
{'https://github.com/Project4': {'HTML': '29', 'Java': '229', 'Markdown': '101', 'Maven POM': '88', 'XML': '62'}}
{'https://github.com/Project5': {'Batchfile': '85', 'Gradle': '84', 'INI': '22', 'Java': '2422', 'Markdown': '25', 'Prolog': '25', 'Shell': '173', 'XML': '3243', 'YAML': '43'}}
Any idea?
You could use pandas :
import pandas as pd
t = [{'https://github.com/project1': {'Batchfile': '91', 'Gradle': '110', 'INI': '25', 'Java': '1879', 'Markdown': '393', 'QMake': '52', 'Shell': '161', 'Text': '202', 'XML': '943'}},
{'https://github.com/project2': {'Batchfile': '91', 'Gradle': '123', 'INI': '25', 'Java': '1305', 'Markdown': '121', 'QMake': '52', 'Shell': '161', 'XML': '234'}},
{'https://github.com/project3': {'Batchfile': '91', 'Gradle': '360', 'INI': '27', 'Java': '805', 'Markdown': '27', 'QMake': '156', 'Shell': '161', 'XML': '380'}}]
columns = set([lang for x in t for l in x.values() for lang in l])
index = [p for x in t for p in x.keys()]
rows = [l for x in t for l in x.values() ]
df = pd.DataFrame(rows, columns=columns, index=index).fillna('N/A')
df.to_csv('projects.csv')
Which gives:
>>> df
Gradle INI Markdown ... Batchfile Java QMake
https://github.com/project1 110 25 393 ... 91 1879 52
https://github.com/project2 123 25 121 ... 91 1305 52
https://github.com/project3 360 27 27 ... 91 805 156
[3 rows x 9 columns]
And in the csv:
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