Objective<\/th>	Method<\/th><\/tr><\/thead>
Track pollution trends on a beach<\/td>	Filter by beach + graph by date<\/td><\/tr>
Compare waste between north\/south beaches<\/td>	Manual selection + histogram<\/td><\/tr>
Identify areas with the most metal<\/td>	lSelection + sorting in the graph<\/td><\/tr>
Create thematic reports by site<\/td>	Successive selections + graph export<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n \n\n\n\n <\/span>Bonus tip: combine with \u00ab\u00a0selection sets<\/span><\/h2>\n\n\n\n Use saved selection groups (menu Selection > Save selection as group) to quickly toggle between several subsets.<\/p>\n\n\n\n \n\n\n\n <\/span>In a nutshell<\/span><\/h2>\n\n\n\n Thanks to interactive selections and filters in QGIS, Data Plotly becomes a true visual analysis dashboard, directly connected to your GIS data. This allows you to:<\/p>\n\n\n\n \n Go beyond simple cartographic display;<\/li>\n\n\n\n Explore correlations, anomalies or local trends;<\/li>\n\n\n\n Produce targeted, exportable visualizations.<\/li>\n<\/ul>\n\n\n\n \n\n\n\n <\/span>What’s next?<\/span><\/h2>\n\n\n\n In the next article, we’ll look at how to automatically export a series of graphs for each entity (beach, commune, etc.), combining QGIS, dynamic expressions and Data Plotly.<\/p>\n\n\n\n \n\n\n\n <\/p>\n","protected":false},"excerpt":{"rendered":" In our previous article, we discovered how to use the Data Plotly plugin to create graphs directly in QGIS. Today, let’s go a step further and learn how to dynamically filter the data displayed in graphs,…<\/p>\n","protected":false},"author":1,"featured_media":14400,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"sfsi_plus_gutenberg_text_before_share":"","sfsi_plus_gutenberg_show_text_before_share":"","sfsi_plus_gutenberg_icon_type":"","sfsi_plus_gutenberg_icon_alignemt":"","sfsi_plus_gutenburg_max_per_row":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_post_was_ever_published":false},"categories":[3394,1377],"tags":[3468,3466,1758,1386],"class_list":["post-14396","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-pluigin-en","category-qgis-en","tag-data-plotly-en","tag-filter","tag-plugin-en","tag-qgis-en"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t

Contenu <\/p>\n Toggle<\/span>

Objective<\/a><\/li>
Starting example: field observations<\/a><\/li>
Step 1: Create a standard graph with Data Plotly<\/a><\/li>
Step 2: Limit analysis to selected entities<\/a><\/li>
Step 3: Filter with an expression<\/a><\/li>
Step 4: alternate selections for comparison<\/a><\/li>
Concrete use cases<\/a><\/li>
Bonus tip: combine with \u00ab\u00a0selection sets<\/a><\/li>
In a nutshell<\/a><\/li>
What’s next?<\/a><\/li><\/ul><\/nav><\/div>\n
<\/span>Objective<\/span><\/h2>\n\n\n\n
Create interactive, context-sensitive graphics to :<\/p>\n\n\n\n
- Visually explore data from field campaigns or environmental observations.<\/li>\n<\/ul>\n\n\n\n
  \n\n\n\n
  <\/span>Starting example: field observations<\/span><\/h2>\n\n\n\n
  Let’s imagine a point layer representing litter surveys on several beaches, with the following fields:<\/p>\n\n\n\n
  \n
  beach: beach name<\/li>\n\n\n\n
  type_of_waste: plastic, metal, glass, etc.<\/li>\n\n\n\n
  quantity: number of objects found<\/li>\n\n\n\n
  date_obs: date of observation<\/li>\n<\/ul>\n\n\n\n
  \n\n\n\n
  <\/span>Step 1: Create a standard graph with Data Plotly<\/span><\/h2>\n\n\n\n
  \n
  Select the survey layer.<\/li>\n\n\n\n
  Launch Extensions > Data Plotly > Data Plotly Panel.<\/li>\n\n\n\n
  Choose a bar plot :\n
  \n
  X : type_dechet<\/li>\n\n\n\n
  Y : quantity<\/li>\n<\/ul>\n<\/li>\n\n\n\n
  Click on Create Plot \u2192 you’ll get a histogram of all observations.<\/li>\n<\/ul>\n\n\n\n
  <\/span>Step 2: Limit analysis to selected entities<\/span><\/h2>\n\n\n\n
  \u27a4 Selection on the map<\/p>\n\n\n\n
  \n
  Activate the selection tool (rectangle, polygon, etc.) in the QGIS toolbar.<\/li>\n\n\n\n
  Select one or more ranges.<\/li>\n<\/ul>\n\n\n\n
  \u27a4 In Data Plotly:<\/p>\n\n\n\n
  \n
  Check the \u201cUse only selected features\u201d box before creating the graph.<\/li>\n\n\n\n
  The graph will only take into account the selected features.<\/li>\n<\/ul>\n\n\n
  \n
  $\"\"$ <\/a><\/figure>\n<\/div>\n\n\n
  Example<\/strong>: this allows you to compare the amount of waste on a single beach, or a targeted area of coastline.<\/p>\n\n\n\n
  \n\n\n\n
  <\/span>Step 3: Filter with an expression<\/span><\/h2>\n\n\n\n
  For more precise analyses, use the Filter tool in the layer:<\/p>\n\n\n\n
  \n
  Right-click on the layer > Filter…<\/li>\n<\/ul>\n\n\n\n
  Filter example:<\/p>\n\n\n\n
  \u201cbeach\u201d = \u2018Anse Mourouk\u2019 AND \u201cdate_obs\u201d >= '2025-01-01'<\/code><\/pre>\n\n\n\n\nApply the filter \u2192 only part of the data remains active.<\/li>\n<\/ul>\n\n\n\nThen create a graph with Data Plotly: it will only take into account the filtered entities, even without manual selection.<\/p>\n\n\n\n \n\n\n\n<\/span>Step 4: alternate selections for comparison<\/span><\/h2>\n\n\n\n\nUseful tip: create several successive graphs, each based on a different selection (e.g. range by range).<\/li>\n\n\n\n You can then save each graph to generate a visual comparison in a report.<\/li>\n<\/ul>\n\n\n\n \n\n\n\n<\/span>Concrete use cases<\/span><\/h2>\n\n\n\nObjective<\/th> Method<\/th><\/tr><\/thead> Track pollution trends on a beach<\/td> Filter by beach + graph by date<\/td><\/tr> Compare waste between north\/south beaches<\/td> Manual selection + histogram<\/td><\/tr> Identify areas with the most metal<\/td> lSelection + sorting in the graph<\/td><\/tr> Create thematic reports by site<\/td> Successive selections + graph export<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n \n\n\n\n<\/span>Bonus tip: combine with \u00ab\u00a0selection sets<\/span><\/h2>\n\n\n\nUse saved selection groups (menu Selection > Save selection as group) to quickly toggle between several subsets.<\/p>\n\n\n\n \n\n\n\n<\/span>In a nutshell<\/span><\/h2>\n\n\n\nThanks to interactive selections and filters in QGIS, Data Plotly becomes a true visual analysis dashboard, directly connected to your GIS data. This allows you to:<\/p>\n\n\n\n \nGo beyond simple cartographic display;<\/li>\n\n\n\n Explore correlations, anomalies or local trends;<\/li>\n\n\n\n Produce targeted, exportable visualizations.<\/li>\n<\/ul>\n\n\n\n \n\n\n\n<\/span>What’s next?<\/span><\/h2>\n\n\n\nIn the next article, we’ll look at how to automatically export a series of graphs for each entity (beach, commune, etc.), combining QGIS, dynamic expressions and Data Plotly.<\/p>\n\n\n\n \n\n\n\n<\/p>\n","protected":false},"excerpt":{"rendered":" In our previous article, we discovered how to use the Data Plotly plugin to create graphs directly in QGIS. Today, let’s go a step further and learn how to dynamically filter the data displayed in graphs,…<\/p>\n","protected":false},"author":1,"featured_media":14400,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"sfsi_plus_gutenberg_text_before_share":"","sfsi_plus_gutenberg_show_text_before_share":"","sfsi_plus_gutenberg_icon_type":"","sfsi_plus_gutenberg_icon_alignemt":"","sfsi_plus_gutenburg_max_per_row":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_post_was_ever_published":false},"categories":[3394,1377],"tags":[3468,3466,1758,1386],"class_list":["post-14396","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-pluigin-en","category-qgis-en","tag-data-plotly-en","tag-filter","tag-plugin-en","tag-qgis-en"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t

<\/span>Objective<\/span><\/h2>\n\n\n\nCreate interactive, context-sensitive graphics to :<\/p>\n\n\n\n\nView only data from a selected area on the map;<\/li>\n\n\n\nDisplay comparisons between different subsets of data;<\/li>\n\n\n\n