docs

docs/source/conf.py

@@ -12,13 +12,13 @@
 #
 import os
 import sys
-sys.path.insert(0, os.path.abspath('../..'))
+sys.path.insert(0, os.path.abspath('../../src'))
 
 
 # -- Project information -----------------------------------------------------
 
 project = 'PyCooRnet'
-copyright = '2020, PyCooRnet Developers'
+copyright = '2021, PyCooRnet Developers'
 author = 'PyCooRnet Developers'
 
 
@@ -53,4 +53,4 @@
 # Add any paths that contain custom static files (such as style sheets) here,
 # relative to this directory. They are copied after the builtin static files,
 # so a file named "default.css" will overwrite the builtin "default.css".
-html_static_path = ['_static']
+#html_static_path = ['_static']

src/pycoornet/crowdtangle.py

@@ -13,8 +13,7 @@
 class CrowdTangle:
     """Descripción de la clase.
 
-        :param api_key: CrowdTangle API key.
-        :type api_key: string
+        api_key (str): CrowdTangle API key.
      """
 
     def __init__(self, api_key):
@@ -29,7 +28,7 @@ def get_shares(self, urls, url_column='url', date_column='date', platforms=('fac
         """ Get the URLs shares from CrowdTangle from a list of URLs with publish datetime
 
         Args:
-            urls (dataframe): a dataframe with at least a column "url" containing the URLs, and a column "date" with their published date
+            urls (pandas.DataFrame): a dataframe with at least a column "url" containing the URLs, and a column "date" with their published date
             url_column (str, optional): name of the column (placed inside quote marks) where the URLs are stored. Defaults to 'url'.
             date_column (str, optional): name of the column (placed inside quote marks) where the date of the URLs are stored. Defaults to 'date'.
             platforms (tuple, optional): a tuple of platforms to search. You can specify only facebook to search on Facebook, or only instagram to
@@ -48,8 +47,7 @@ def get_shares(self, urls, url_column='url', date_column='date', platforms=('fac
             SystemExit: [description]
 
         Returns:
-            [pandas.Dataframe]: [A pandas dataframe of posts that shared the URLs and a number of variables returned by the https://github.com/CrowdTangle/API/wiki/Links
-                    CrowdTangle API links endpoint and the original data set of news.
+            pandas.DataFrame: A pandas dataframe of posts that shared the URLs and a number of variables returned by the https://github.com/CrowdTangle/API/wiki/Links CrowdTangle API links endpoint and the original data set of news.
         """
 
         try:

src/pycoornet/shared.py

@@ -18,10 +18,6 @@ class Shared:
     Args:
         crowdtangle_shares_df (pandas.DataFrame): the pandas dataframe of link posts resulting from the function
                 CrowdTangle shares
-    Returns:
-        2-elementos tuple containing
-        - **graph** (networkx.Graph): An graph (highly_connected_g) with networks of coordinated entities whose edges also contains a t_coord_share attribute (vector) reporting the timestamps of every time the edge was detected as coordinated sharing.
-        - **q** (float): Percentile edge weight number of leeped repetedly coordinated link sharing.
     """
     def __init__(self, crowdtangle_shares_df):
         self.__crowdtangle_shares_df = crowdtangle_shares_df
@@ -45,9 +41,10 @@ def estimate_coord_interval(self, q=0.1, p=0.5, clean_urls=False, keep_ourl_only
             keep_ourl_only (bool, optional): restrict the analysis to CrownTangle shares links matching the original URLs. Defaults to False.
 
         Returns:
-            2-element tuple containing
-            - **summary** (pandas.DataFrame): summary statistics of q\% quickest second share performing URLs.
-            - **coordination interval** (integer): time in seconds corresponding to the median time spent by these URLs to cumulate the % of their total shares.
+            (tuple): 2-element tuple containing
+
+                - **summary** (pandas.DataFrame): summary statistics of q\% quickest second share performing URLs.
+                - **coordination interval** (integer): time in seconds corresponding to the median time spent by these URLs to cumulate the % of their total shares.
         """
         if 0<p<1 == False:
             logger.error('The p value must be between 0 and 1')
@@ -279,11 +276,11 @@ def coord_shares(self, coordination_interval=None, percentile_edge_weight=90, cl
                 Slow on large networks. Defaults to False.
 
         Returns:
-            3-element tuple containing
+            (tuple): 3-element tuple containing
 
-            - **coordinated_df** (pandas.DataFrame): The input dataframe of shares with an additional boolean variable (coordinated) that identifies coordinated shares.
-            - **graph** (networkx.Graph): An graph (highly_connected_g) with networks of coordinated entities whose edges also contains a t_coord_share attribute (vector) reporting the timestamps of every time the edge was detected as coordinated sharing.
-            - **q** (networkx.Graph): Percentile edge weight number of leeped repetedly coordinated link sharing.
+                - **coordinated_df** (pandas.DataFrame): The input dataframe of shares with an additional boolean variable (coordinated) that identifies coordinated shares.
+                - **graph** (networkx.Graph): An graph (highly_connected_g) with networks of coordinated entities whose edges also contains a t_coord_share attribute (vector) reporting the timestamps of every time the edge was detected as coordinated sharing.
+                - **q** (networkx.Graph): Percentile edge weight number of leeped repetedly coordinated link sharing.
         """
         # estimate the coordination interval if not specified by the users
         dataframe = self.__crowdtangle_shares_df.copy(deep=True)

src/pycoornet/utils.py

@@ -9,7 +9,7 @@ def clean_urls(dataframe, url_column):
 
         Args:
             dataframe (pandas.DataFrame): the pandas dataframe of link posts
-            url_column (string): the name of the dataframe column with the urls
+            url_column (str): the name of the dataframe column with the urls
 
         Returns:
             pandas.DataFrame: the dateframe with the cleaned urls