| WARNING: This repo is under test ! |
|---|
The main objective is to write an automatic report to facilitate the analysis of a twitter graph.
| Twitter-graph : To know how to make a twitter-graph, look eleurent's repo: |
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Testing with python3.8
Need pip packages:
| pip packages | tested version |
|---|---|
| python-docx | 0.8.11 |
| numpy | 1.19.5 |
| pandas | 0.25.3 |
| igraph | 0.9.9 |
| textdistance | 4.2.2 |
| matplotlib | 3.4.2 |
Install requirements with :
pip3 install -r requirements.txt
from autoReport import *
autoReport("nodes.csv", "edges.csv",
{2339:"magenta",
2433:"limegreen",
2566:"deepskyblue",
1052:"saddlebrown",
2498:"darkorange",
1583:"red"},
{"name":"Antoine Bondaz",
"at":"@AntoineBondaz",
"description":"""Foodie - 🕵🏼Research @FRS_org - 👨🏼🏫 Teach @SciencesPo - 🇨🇳🇹🇼🇰🇷🇰🇵's foreign & security policies - Ph.D."""},
rank_col_name="pageranks",
class_col_name="modularity_class",
).makeReport("out.docx",
per_edeges=1,
show_internal_link=False)Creates a report out.docx for Antoine Bondaz, with 6 class. nodes.csv have two columns : one with the rank of the nodes (default pageranks) and one with class (default modularity_class). If columns have special name, specify the argument class_col_name for class columns name and rank_col_name for rank column name in the construct.
- If your graph comes from the tweets search, you can add the tweets.json file with the tweets_path parameter (on the constructor) to have more graphics.
- To test quickly, you can add the per_edeges=0.1 parameter (to the makeReport method) to test the link graph with 10% of edges. Important to verify the correct installation of igraph
If the size of the nodes is calculated with In-Degree and In-Degree is not in the columns of the csv nodes, you can specify InDegree for the rank_col_name parameter, it will calculate it.
The report is divided into 2 parts: the first one looks at the whole graph, the second one at each class.
