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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+.gradio/flagged/dataset1.csv filter=lfs diff=lfs merge=lfs -text

.gradio/flagged/dataset1.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6c0626727df0ba581be5a6b356ee5864fddade8afd93b5339d578fc48223a451
+size 19623678

Chart 1.csv

@@ -0,0 +1,40 @@
+Country you practice in,count(Screening Number),Screening Number
+Pakistan,266,0SC-2865460SC-2873130SC-2873177SC-2873178SC-2873181SC-2881387SC-2881391SC-2881394SC-2881396SC-2881401SC-2881403SC-2881404SC-2881405SC-2881482SC-2881542SC-2881545SC-2881551SC-2881558SC-2881559SC-2881561SC-2881565SC-2881606SC-2881691SC-2881827SC-2881849SC-2881870SC-2881884SC-2884635SC-2884637SC-2884642SC-2884643SC-2884644SC-2884647SC-2884648SC-2884649SC-2884650SC-2884654SC-2884655SC-2884658SC-2884659SC-2884660SC-2884664SC-2884666SC-2884667SC-2884669SC-2884673SC-2884677SC-2884684SC-2884686SC-2884691SC-2884697SC-2884698SC-2884699SC-2884702SC-2884704SC-2884708SC-2884710SC-2884714SC-2884723SC-2884727SC-2884745SC-2884747SC-2884748SC-2884751SC-2884753SC-2884754SC-2884756SC-2884772SC-2884773SC-2884776SC-2884783SC-2884790SC-2884792SC-2884799SC-2884804SC-2884839SC-2884842SC-2884847SC-2884922SC-2884957SC-2884958SC-2884966SC-2884969SC-2885006SC-2885076SC-2885236SC-2885260SC-2885340SC-2885354SC-2885355SC-2885360SC-2885361SC-2885362SC-2885364SC-2885368SC-2885371SC-2885406SC-2885411SC-2885421SC-2885571SC-2885663SC-2885664SC-2885683SC-2885848SC-2889628SC-2892846SC-2894692SC-2894793SC-2895740SC-2902242SC-2902468SC-2908466SC-2923608SC-2925268SC-2925276SC-2925280SC-2925281SC-2925282SC-2925284SC-2925285SC-2925289SC-2925291SC-2925293SC-2925301SC-2925303SC-2925311SC-2925312SC-2925315SC-2925318SC-2925321SC-2925325SC-2925333SC-2925346SC-2925349SC-2925351SC-2925356SC-2925357SC-2925358SC-2925364SC-2925366SC-2925367SC-2925371SC-2925385SC-2925404SC-2925414SC-2925416SC-2925419SC-2925421SC-2925423SC-2925424SC-2925425SC-2925429SC-2925431SC-2925432SC-2925440SC-2925443SC-2925449SC-2925450SC-2925455SC-2925460SC-2925462SC-2925467SC-2925472SC-2925473SC-2925474SC-2925475SC-2925478SC-2925481SC-2925482SC-2925487SC-2925492SC-2925493SC-2925499SC-2925505SC-2925552SC-2925567SC-2925592SC-2925593SC-2925594SC-2925595SC-2925597SC-2925598SC-2925599SC-2925601SC-2925604SC-2925605SC-2925607SC-2925610SC-2925611SC-2925612SC-2925613SC-2925616SC-2925617SC-2925618SC-2925619SC-2925620SC-2925621SC-2925622SC-2925623SC-2925625SC-2925626SC-2925627SC-2925628SC-2925630SC-2925631SC-2925632SC-2925633SC-2925634SC-2925636SC-2925637SC-2925639SC-2925641SC-2925642SC-2925643SC-2925644SC-2925645SC-2925648SC-2925649SC-2925652SC-2925653SC-2925654SC-2925655SC-2925657SC-2925658SC-2925659SC-2925661SC-2925662SC-2925674SC-2925688SC-2925700SC-2925710SC-2925730SC-2925748SC-2925756SC-2925759SC-2925760SC-2925763SC-2925764SC-2925770SC-2925774SC-2925783SC-2925828SC-2925852SC-2925855SC-2925859SC-2925862SC-2925863SC-2925864SC-2925865SC-2925867SC-2925868SC-2925872SC-2925892SC-2925894SC-2925913SC-2925915SC-2925948SC-2926261SC-2926431SC-2926692SC-2926763SC-2926969SC-2927121SC-2927158SC-2927264SC-2927724
+USA,56,0SC-2872943SC-2872953SC-2872956SC-2872958SC-2872978SC-2872986SC-2873016SC-2873024SC-2873029SC-2873033SC-2873042SC-2873070SC-2873073SC-2873075SC-2873129SC-2873132SC-2873182SC-2873185SC-2873187SC-2873188SC-2873194SC-2873229SC-2881022SC-2881633SC-2881787SC-2882948SC-2884324SC-2885539SC-2885540SC-2885577SC-2885590SC-2885642SC-2885647SC-2885648SC-2885649SC-2885662SC-2885950SC-2886000SC-2889775SC-2889817SC-2889891SC-2895727SC-2900473SC-2911925SC-2911930SC-2911938SC-2912012SC-2912105SC-2912334SC-2912647SC-2912909SC-2919726SC-2919792SC-2922152SC-2923607SC-2926104
+Canada,2,0SC-2872948SC-2894797
+Ethiopia,1,0SC-2872964
+Ukraine,4,0SC-2872968SC-2881840SC-2885507SC-2912027
+Barbados,1,0SC-2872991
+Nigeria,5,0SC-2873000SC-2881318SC-2881372SC-2895730SC-2912101
+Panama,2,0SC-2873018SC-2911919
+Puerto Rico,3,0SC-2873064SC-2911916SC-2912070
+India,60,0SC-2873067SC-2882043SC-2884687SC-2884688SC-2884689SC-2884692SC-2884717SC-2884731SC-2884734SC-2884735SC-2884736SC-2884758SC-2884774SC-2884825SC-2884865SC-2885052SC-2885326SC-2885328SC-2885329SC-2885331SC-2885345SC-2885347SC-2885348SC-2885357SC-2885490SC-2895729SC-2895741SC-2895742SC-2895746SC-2895768SC-2895775SC-2901388SC-2911923SC-2911927SC-2925570SC-2927780SC-2927782SC-2927784SC-2927788SC-2927790SC-2927791SC-2927792SC-2927793SC-2927794SC-2927798SC-2927799SC-2927800SC-2927801SC-2927802SC-2927803SC-2927804SC-2927805SC-2927807SC-2927808SC-2927811SC-2927821SC-2927822SC-2927823SC-2927867SC-2927875
+Peru,3,0SC-2873068SC-2881432SC-2885993
+Iraq,1,0SC-2873076
+Jordan,5,0SC-2873078SC-2927824SC-2928572SC-2929522SC-2929815
+Ghana,4,0SC-2881223SC-2881407SC-2882144SC-2911924
+South Africa,6,0SC-2881285SC-2881321SC-2881411SC-2885521SC-2885881SC-2927674
+Guatemala,2,0SC-2881299SC-2912092
+Nicaragua,1,0SC-2881310
+Haiti,1,0SC-2881475
+china,1,0SC-2881514
+Argentina,2,0SC-2881705SC-2898746
+Australia,1,0SC-2881726
+Vietnam,1,0SC-2881878
+Namibia,1,0SC-2881919
+Rwanda,3,0SC-2882150SC-2882610SC-2886018
+Papua New Guinea,1,0SC-2882912
+Kuwait,1,0SC-2884678
+UAE,2,0SC-2884695SC-2925650
+Malawi,6,0SC-2885384SC-2932564SC-2932565SC-2932586SC-2932642SC-2932782
+Nepal,1,0SC-2885462
+Brazil,5,0SC-2885497SC-2899504SC-2899910SC-2909890SC-2931811
+dominican republic,1,0SC-2885506
+Mexico,6,0SC-2885530SC-2885536SC-2911968SC-2912020SC-2912148SC-2931850
+Bosnia and Herzegovina,1,0SC-2885624
+Thailand,2,0SC-2885715SC-2904697
+Indonesia,3,0SC-2885855SC-2885871SC-2889637
+Ecuador,2,0SC-2895401SC-2931813
+Oman,3,0SC-2895467SC-2895494SC-2895751
+Colombia,1,0SC-2911959
+Venezuela,1,0SC-2912062

README.md

@@ -1,12 +1,6 @@
 ---
-title: PyGwalker Dashboard
-emoji: 👁
-colorFrom: purple
-colorTo: gray
-sdk: gradio
-sdk_version: 5.9.1
+title: PyGwalker_dashboard
 app_file: app.py
-pinned: false
+sdk: gradio
+sdk_version: 5.0.2
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,35 @@
+import pandas as pd
+import pygwalker as pyg
+import gradio as gr
+
+#df = pd.read_csv("C:\\Users\\tooba.alvi\\OneDrive - Aga Khan University\\Documents\\GitHub\\PyG Walker\\WorldBank.csv", encoding= "utf-8")
+url="https://raw.githubusercontent.com/ToobaAhmedAlvi/PyG_Walker_dashboard/main/WorldBank.csv"
+df = pd.read_csv(url, index_col=0)
+    
+# Define a function to create the dashboard
+'''
+def create_dashboard():
+    df = pd.read_csv("C:\\Users\\tooba.alvi\\OneDrive - Aga Khan University\\Documents\\GitHub\\PyG Walker\\WorldBank.csv", encoding= "utf-8")
+    pyg.walk(df)
+   return pyg.get_html()
+'''
+
+def display_data():
+    url="https://raw.githubusercontent.com/ToobaAhmedAlvi/PyG_Walker_dashboard/main/WorldBank.csv"
+    df = pd.read_csv(url, index_col=0)
+    #df = pd.read_csv("C:\\Users\\tooba.alvi\\OneDrive - Aga Khan University\\Documents\\GitHub\\PyG Walker\\WorldBank.csv", encoding= "utf-8")
+    df=pd.DataFrame(df)
+    pyg.walk(df)
+    pyg_html = pyg.to_html(df)
+    vis_spec=r"""{"config":[{"config":{"defaultAggregated":true,"geoms":["auto"],"coordSystem":"generic","limit":-1,"timezoneDisplayOffset":0},"encodings":{"dimensions":[{"fid":"Year","name":"Year","basename":"Year","analyticType":"dimension","semanticType":"ordinal","aggName":"sum","offset":0},{"fid":"Country Name","name":"Country Name","basename":"Country Name","semanticType":"nominal","analyticType":"dimension","offset":0},{"fid":"Country Code","name":"Country Code","basename":"Country Code","semanticType":"nominal","analyticType":"dimension","offset":0},{"fid":"Region","name":"Region","basename":"Region","semanticType":"nominal","analyticType":"dimension","offset":0},{"fid":"IncomeGroup","name":"IncomeGroup","basename":"IncomeGroup","semanticType":"nominal","analyticType":"dimension","offset":0},{"fid":"gw_mea_key_fid","name":"Measure names","analyticType":"dimension","semanticType":"nominal"}],"measures":[{"fid":"Birth rate, crude (per 1,000 people)","name":"Birth rate, crude (per 1,000 people)","basename":"Birth rate, crude (per 1,000 people)","analyticType":"measure","semanticType":"quantitative","aggName":"sum","offset":0},{"fid":"Death rate, crude (per 1,000 people)","name":"Death rate, crude (per 1,000 people)","basename":"Death rate, crude (per 1,000 people)","analyticType":"measure","semanticType":"quantitative","aggName":"sum","offset":0},{"fid":"Electric power consumption (kWh per capita)","name":"Electric power consumption (kWh per capita)","basename":"Electric power consumption (kWh per capita)","analyticType":"measure","semanticType":"quantitative","aggName":"sum","offset":0},{"fid":"GDP (USD)","name":"GDP (USD)","basename":"GDP (USD)","analyticType":"measure","semanticType":"quantitative","aggName":"sum","offset":0},{"fid":"GDP per capita (USD)","name":"GDP per capita (USD)","basename":"GDP per capita (USD)","analyticType":"measure","semanticType":"quantitative","aggName":"sum","offset":0},{"fid":"Individuals using the Internet (% of population)","name":"Individuals using the Internet (% of population)","basename":"Individuals using the Internet (% of population)","analyticType":"measure","semanticType":"quantitative","aggName":"sum","offset":0},{"fid":"Infant mortality rate (per 1,000 live births)","name":"Infant mortality rate (per 1,000 live births)","basename":"Infant mortality rate (per 1,000 live births)","analyticType":"measure","semanticType":"quantitative","aggName":"sum","offset":0},{"fid":"Life expectancy at birth (years)","name":"Life expectancy at birth (years)","basename":"Life expectancy at birth (years)","analyticType":"measure","semanticType":"quantitative","aggName":"sum","offset":0},{"fid":"Population density (people per sq. km of land area)","name":"Population density (people per sq. km of land area)","basename":"Population density (people per sq. km of land area)","analyticType":"measure","semanticType":"quantitative","aggName":"sum","offset":0},{"fid":"Unemployment (% of total labor force) (modeled ILO estimate)","name":"Unemployment (% of total labor force) (modeled ILO estimate)","basename":"Unemployment (% of total labor force) (modeled ILO estimate)","analyticType":"measure","semanticType":"quantitative","aggName":"sum","offset":0},{"fid":"gw_count_fid","name":"Row count","analyticType":"measure","semanticType":"quantitative","aggName":"sum","computed":true,"expression":{"op":"one","params":[],"as":"gw_count_fid"}},{"fid":"gw_mea_val_fid","name":"Measure values","analyticType":"measure","semanticType":"quantitative","aggName":"sum"}],"rows":[{"fid":"Birth rate, crude (per 1,000 people)","name":"Birth rate, crude (per 1,000 people)","basename":"Birth rate, crude (per 1,000 people)","analyticType":"measure","semanticType":"quantitative","aggName":"mean","offset":0}],"columns":[{"fid":"Year","name":"Year","basename":"Year","analyticType":"dimension","semanticType":"ordinal","aggName":"sum","offset":0}],"color":[{"fid":"IncomeGroup","name":"IncomeGroup","basename":"IncomeGroup","semanticType":"nominal","analyticType":"dimension","offset":0}],"opacity":[],"size":[],"shape":[],"radius":[],"theta":[],"longitude":[],"latitude":[],"geoId":[],"details":[],"filters":[{"fid":"IncomeGroup","name":"IncomeGroup","basename":"IncomeGroup","semanticType":"nominal","analyticType":"dimension","offset":0,"rule":null}],"text":[]},"layout":{"showActions":false,"showTableSummary":false,"stack":"stack","interactiveScale":false,"zeroScale":true,"size":{"mode":"auto","width":320,"height":200},"format":{},"geoKey":"name","resolve":{"x":false,"y":false,"color":false,"opacity":false,"shape":false,"size":false}},"visId":"gw_DGUp","name":"Chart 1"}],"chart_map":{},"workflow_list":[{"workflow":[{"type":"view","query":[{"op":"aggregate","groupBy":["Year","IncomeGroup"],"measures":[{"field":"Birth rate, crude (per 1,000 people)","agg":"mean","asFieldKey":"Birth rate, crude (per 1,000 people)_mean"}]}]}]}],"version":"0.4.8.10"}"""
+    return pyg_html
+
+
+# Create a Gradio interface
+interface = gr.Interface(fn=display_data,
+                        inputs=[],
+                        outputs="html",  
+                        title="My Dashboard with PyG Walker")
+
+# Launch the interface
+interface.launch(share='True')

requirements.txt

@@ -0,0 +1,3 @@
+gradio
+pygwalker
+pandas