csv2gexf/app.py

197 lines
6.3 KiB
Python

import networkx as nx
import pandas as pd
import streamlit as st
import info
def add_edges(G, df, source, target, chosen_columns):
# Iterate over each row in the DataFrame and add an edge to the graph.
attrs = {}
for key, row in df.iterrows():
# Add edge with key.
G.add_edge(row[source], row[target], key)
# Set attributes for edge.
d_attrs = {}
for column in chosen_columns:
try:
d_attrs[column] = int(row[column])
except ValueError:
d_attrs[column] = row[column]
attrs[(row[source], row[target], key)] = d_attrs
# Add the attributes to the edges.
nx.set_edge_attributes(G, attrs)
return G
def add_nodes(G, df):
"""Add nodes to the graph."""
d = df.to_dict(orient="index")
nodes = [(k, v) for k, v in d.items()]
G.add_nodes_from(nodes)
return G
def find_columns(column, columns):
if column in columns:
selected = column
else:
columns.append('')
selected = ''
# Let user select target.
selected = st.selectbox(
label = f"Which one is the {column} column?",
options=columns,
format_func=lambda x: 'Select an option' if x == '' else x,
index=columns.index(selected),
key=column
)
return selected
# Set oage config and CSS.
st.set_page_config(page_title='CSV→Gephi', page_icon='🎭')
st.markdown(info.css, unsafe_allow_html=True)
# Print title.
st.title("Make :green[Gephi] from :red[CSV]")
# Print tagline.
st.markdown(
"""*Upload your data as CSV to make it into a GraphML-file compatible
with Gephi and [Gephi Light](https://gephi.org/gephi-lite/).*"""
)
#try:
# Print explainer.
expl = st.expander(label="More info")
with expl:
st.write(info.explainer)
# Ask for nodes file.
csv_nodes = st.file_uploader(
label="Upload file with **nodes** (if you have one).", key="nodes", help=f'[Example]({info.node_example})'
)
# Ask for relations file.
csv_edges = st.file_uploader(label="Upload file with **edges/relations**.", key="relations", help=f'[Example]({info.relations_example})')
col1, col2 = st.columns([1,2])
# Chose separator
with col1:
# Set standard separator.
st.session_state["sep"] = ','
# Ask for separator.
separators = {'comma ( , )': ',', 'semicolon ( ; )': ';', 'tab ( \u21E5 )': '\t', 'pipe (|)': '|', 'space ( )': ' ', '':''}
sep = st.radio(
'Separator in your files:',
options=['comma ( , )', 'semicolon ( ; )', 'tab ( \u21E5 )', 'pipe (|)', 'space ( )', 'custom'],
help='What are the values in your files separated with?'
)
if sep == 'custom':
sep = st.text_input('Custom delimiter:')
separators[sep] = sep
st.session_state["sep"] = separators[sep]
# Preview file
with col2:
preview = st.button('Preview file.')
if preview:
try:
st.dataframe(pd.read_csv(csv_edges, sep=st.session_state["sep"]), use_container_width=True)
except pd.errors.ParserError:
st.markdown(':red[Have you selected a correct separator?]')
files_uploaded = st.button('Done', 'files_uploaded')
if files_uploaded or 'files_already_uploaded' in st.session_state:
st.session_state['files_already_uploaded'] = True
if csv_edges == None:
st.markdown(':red[You need to upload a file with relations.]')
st.stop()
try:
df = pd.read_csv(csv_edges, sep=st.session_state["sep"])
except pd.errors.EmptyDataError:
st.markdown(':red[Have you chosen the right kind of separator?]')
st.stop()
df.rename({'type': 'relation_type'}, inplace=True, axis=1) # 'type' can't be used as attribute.
df.columns = [i.lower() for i in df.columns] # Remove capital letters from column names.
# Find and store target column.
target = find_columns('target', df.columns.tolist())
# Find and store source column.
source = find_columns('source', df.columns.tolist())
# Remove source and target columns from list of options.
columns = df.columns.tolist()
columns.remove(st.session_state["target"])
columns.remove(st.session_state["source"])
if all([st.session_state["source"] != "", st.session_state["target"] != ""]):
source = st.session_state["source"]
target = st.session_state["target"]
# Let the user chose what columns that should be included.
chosen_columns = st.multiselect(
label="Chose other columns to include.", options=columns, default=columns
)
if csv_nodes != None: # When a nodes file is uploaded.
df_nodes = pd.read_csv(csv_nodes, sep=st.session_state["sep"])
df_nodes.columns = [i.lower() for i in df_nodes.columns] # Remove capital letters from column names.
st.session_state['label_column'] = find_columns('label', df_nodes.columns.tolist())
if st.session_state['label_column'] != '':
df_nodes.set_index(st.session_state['label_column'], inplace=True)
else: # If no node file provided.
nodes = list(set(df[source].tolist() + df[target].tolist()))
df_nodes = pd.DataFrame(
nodes, index=range(0, len(nodes)), columns=["labels"]
)
st.session_state['label_column'] = 'labels'
if st.session_state['label_column'] != '' and df_nodes.index.name != st.session_state['label_column']:
df_nodes.set_index(st.session_state['label_column'], inplace=True)
# Make empty graph.
G = nx.MultiDiGraph()
# Add nodes.
G = add_nodes(G, df_nodes)
# Add edges.
G = add_edges(
G, df, source=source, target=target, chosen_columns=chosen_columns
)
# Turn the graph into a string.
graph_text = "\n".join([line for line in nx.generate_graphml(G)])
# Download graphml-file.
graphml_file = "output.graphml"
st.download_button(
"Download grampml-file", graph_text, file_name=graphml_file
)
st.write('Import the file to Gephi/Gephi Light, or try [Gephisto](https://jacomyma.github.io/gephisto/) to get an idea of the network.')
# except:
# st.markdown(':red[Something went wrong, please try again or [write to me](https://twitter.com/lasseedfast).]')