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Dataframe examples problem #10723

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caglarari opened this issue Mar 4, 2025 · 5 comments
Closed
1 task done

Dataframe examples problem #10723

caglarari opened this issue Mar 4, 2025 · 5 comments
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bug Something isn't working 💾 Dataframe needs repro Awaiting full reproduction

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@caglarari
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Describe the bug

The code below that uses Gradio dataframe with pandas dataframe examples used to work but I tried it on Hugging Face & it doesn't work anymore. It doesn't work with an older Gradio version 3.50.2 either. When I tried it with version 3.50.2, Gradio treated the first row of the pandas data frame as string / header but it shouldn't since Xhpd=pd.read_csv("data_NB.csv",header=None)

Any idea how can I fix this problem?

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from copy import deepcopy

import time

import gradio as gr

plt.rcParams['figure.figsize'] = [10, 10]
plt.rcParams['figure.dpi'] = 100

Xhpd=pd.read_csv("data_NB.csv",header=None)
yhpd=pd.read_csv("labels_NB.csv",header=None)

def visualise_gr(models,names,lsData,inTitle="Data Set",kNum=200,th=0.001):
fig=plt.figure()
plt.scatter(lsData[0][:,0],lsData[0][:,1], color='red')
plt.scatter(lsData[1][:,0],lsData[1][:,1], color='blue')
plt.xticks(range(0,11))
plt.yticks(range(0,11))
plt.xlabel("X")
plt.ylabel("Y")
plt.grid()
plt.title(inTitle)
#
plt.axis('scaled')
print("visualize gr")
return fig

def user_greeting2(inLogregC,inGNBC,inM,dfData,dfLabs):
X=dfData.to_numpy(dtype=np.float64)
y=dfLabs.to_numpy(dtype=np.float64)
y=y.reshape((y.shape[1],))
#
print("X dims",X.shape)
print("y dims",y.shape)
#
#
labnos=np.unique(y)
labnos=np.int32(labnos)
kK=labnos.shape[0]
lsData=[]
lslabs=[]
for k in range(kK):
yk=y[y==labnos[k]]
datak=X[y==labnos[k],:]
lsData.append(datak)
lslabs.append(yk)
#
strTitle='Title'
fig2=visualise_gr([],[],lsData,inTitle=strTitle,th=0.001,kNum=90)
#
strTitle2='Title2'
fig3=visualise_gr([],[],lsData,inTitle=strTitle2,kNum=90)
#
fig1=visualise_gr([],[],lsData)
return fig1,fig2,fig3

def user_greeting1(inLogregC,inGNBC,inM,dfData,dfLabs):
#
print('dbg 1 in')
print(dfData)
print(dfLabs)
#
X=dfData.to_numpy(dtype=np.float64)
y=dfLabs.to_numpy(dtype=np.float64)
y=y.reshape((y.shape[1],))
#
print('dbg 1 after to_numpy')
print("X dims",X.shape)
print("y dims",y.shape)
#
labnos=np.unique(y)
labnos=np.int32(labnos)
kK=labnos.shape[0]
lsData=[]
lslabs=[]
for k in range(kK):
yk=y[y==labnos[k]]
datak=X[y==labnos[k],:]
lsData.append(datak)
lslabs.append(yk)
#
strTitle="Title1"
fig2=visualise_gr([],[],lsData,inTitle=strTitle,th=0.001,kNum=200)
#
strTitle2="Title2"
fig3=visualise_gr([],[],lsData,inTitle=strTitle2,kNum=200)

fig1=visualise_gr([],[],lsData)
return fig1,fig2,fig3

inputs1 = [ gr.Number(label='xxx C'),gr.Number(label='yyy C'),gr.Number(label='mmm'),
gr.Dataframe(row_count = (3, "dynamic"), col_count=(4,"dynamic"), label="Labeled Data", interactive=1),
gr.Dataframe(row_count = (1, "fixed"), col_count=(4,"dynamic"), label="Labels", interactive=1),
]

outputs1=[gr.Plot(),gr.Plot(),gr.Plot()]

app1 = gr.Interface(fn = user_greeting1, inputs=inputs1, outputs=outputs1, examples =[['1.0','10.0','0.001', 'data_NB.csv', 'labels_NB.csv']])

inputs2 = [ gr.Number(label='xxx C'),gr.Number(label='yyy C'),gr.Number(label='mmm'),
gr.Dataframe(row_count = (3, "dynamic"), col_count=(4,"dynamic"), label="Labeled Data", interactive=1),
gr.Dataframe(row_count = (1, "fixed"), col_count=(4,"dynamic"), label="Labels", interactive=1),
]

outputs2=[gr.Plot(),gr.Plot(),gr.Plot()]

app2 = gr.Interface(fn = user_greeting2, inputs=inputs2, outputs=outputs2,examples =[[1.0,1.0,0.001, Xhpd,yhpd]])

demo = gr.TabbedInterface([app1, app2], ["App1", "App2"])
#demo.launch(share=True)
demo.launch(share=False)

Have you searched existing issues? 🔎

  • I have searched and found no existing issues

Reproduction

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from copy import deepcopy

import time

import gradio as gr

plt.rcParams['figure.figsize'] = [10, 10]
plt.rcParams['figure.dpi'] = 100

Xhpd=pd.read_csv("data_NB.csv",header=None)
yhpd=pd.read_csv("labels_NB.csv",header=None)

def visualise_gr(models,names,lsData,inTitle="Data Set",kNum=200,th=0.001):
fig=plt.figure()
plt.scatter(lsData[0][:,0],lsData[0][:,1], color='red')
plt.scatter(lsData[1][:,0],lsData[1][:,1], color='blue')
plt.xticks(range(0,11))
plt.yticks(range(0,11))
plt.xlabel("X")
plt.ylabel("Y")
plt.grid()
plt.title(inTitle)
#
plt.axis('scaled')
print("visualize gr")
return fig

def user_greeting2(inLogregC,inGNBC,inM,dfData,dfLabs):
X=dfData.to_numpy(dtype=np.float64)
y=dfLabs.to_numpy(dtype=np.float64)
y=y.reshape((y.shape[1],))
#
print("X dims",X.shape)
print("y dims",y.shape)
#
#
labnos=np.unique(y)
labnos=np.int32(labnos)
kK=labnos.shape[0]
lsData=[]
lslabs=[]
for k in range(kK):
yk=y[y==labnos[k]]
datak=X[y==labnos[k],:]
lsData.append(datak)
lslabs.append(yk)
#
strTitle='Title'
fig2=visualise_gr([],[],lsData,inTitle=strTitle,th=0.001,kNum=90)
#
strTitle2='Title2'
fig3=visualise_gr([],[],lsData,inTitle=strTitle2,kNum=90)
#
fig1=visualise_gr([],[],lsData)
return fig1,fig2,fig3

def user_greeting1(inLogregC,inGNBC,inM,dfData,dfLabs):
#
print('dbg 1 in')
print(dfData)
print(dfLabs)
#
X=dfData.to_numpy(dtype=np.float64)
y=dfLabs.to_numpy(dtype=np.float64)
y=y.reshape((y.shape[1],))
#
print('dbg 1 after to_numpy')
print("X dims",X.shape)
print("y dims",y.shape)
#
labnos=np.unique(y)
labnos=np.int32(labnos)
kK=labnos.shape[0]
lsData=[]
lslabs=[]
for k in range(kK):
yk=y[y==labnos[k]]
datak=X[y==labnos[k],:]
lsData.append(datak)
lslabs.append(yk)
#
strTitle="Title1"
fig2=visualise_gr([],[],lsData,inTitle=strTitle,th=0.001,kNum=200)
#
strTitle2="Title2"
fig3=visualise_gr([],[],lsData,inTitle=strTitle2,kNum=200)

fig1=visualise_gr([],[],lsData)
return fig1,fig2,fig3

inputs1 = [ gr.Number(label='xxx C'),gr.Number(label='yyy C'),gr.Number(label='mmm'),
gr.Dataframe(row_count = (3, "dynamic"), col_count=(4,"dynamic"), label="Labeled Data", interactive=1),
gr.Dataframe(row_count = (1, "fixed"), col_count=(4,"dynamic"), label="Labels", interactive=1),
]

outputs1=[gr.Plot(),gr.Plot(),gr.Plot()]

app1 = gr.Interface(fn = user_greeting1, inputs=inputs1, outputs=outputs1, examples =[['1.0','10.0','0.001', 'data_NB.csv', 'labels_NB.csv']])

inputs2 = [ gr.Number(label='xxx C'),gr.Number(label='yyy C'),gr.Number(label='mmm'),
gr.Dataframe(row_count = (3, "dynamic"), col_count=(4,"dynamic"), label="Labeled Data", interactive=1),
gr.Dataframe(row_count = (1, "fixed"), col_count=(4,"dynamic"), label="Labels", interactive=1),
]

outputs2=[gr.Plot(),gr.Plot(),gr.Plot()]

app2 = gr.Interface(fn = user_greeting2, inputs=inputs2, outputs=outputs2,examples =[[1.0,1.0,0.001, Xhpd,yhpd]])

demo = gr.TabbedInterface([app1, app2], ["App1", "App2"])
#demo.launch(share=True)
demo.launch(share=False)

data_NB.csv

labels_NB.csv

Screenshot

No response

Logs

Traceback (most recent call last):
  File "/home/user/app/app.py", line 114, in <module>
    app2 =  gr.Interface(fn = user_greeting2, inputs=inputs2, outputs=outputs2,examples =[[1.0,1.0,0.001, Xhpd,yhpd]])
  File "/usr/local/lib/python3.10/site-packages/gradio/interface.py", line 546, in __init__
    self.render_examples()
  File "/usr/local/lib/python3.10/site-packages/gradio/interface.py", line 904, in render_examples
    self.examples_handler = Examples(
  File "/usr/local/lib/python3.10/site-packages/gradio/helpers.py", line 57, in create_examples
    examples_obj = Examples(
  File "/usr/local/lib/python3.10/site-packages/gradio/helpers.py", line 265, in __init__
    self.dataset = components.Dataset(
  File "/usr/local/lib/python3.10/site-packages/gradio/component_meta.py", line 181, in wrapper
    return fn(self, **kwargs)
  File "/usr/local/lib/python3.10/site-packages/gradio/components/dataset.py", line 118, in __init__
    ex = component.as_example(ex)
  File "/usr/local/lib/python3.10/site-packages/gradio/components/base.py", line 309, in as_example
    return self.process_example(value)
  File "/usr/local/lib/python3.10/site-packages/gradio/components/dataframe.py", line 507, in process_example
    value_df_data = self.postprocess(value)
  File "/usr/local/lib/python3.10/site-packages/gradio/components/dataframe.py", line 431, in postprocess
    return DataframeData(
  File "/usr/local/lib/python3.10/site-packages/pydantic/main.py", line 214, in __init__
    validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)
pydantic_core._pydantic_core.ValidationError: 2 validation errors for DataframeData
headers.0
  Input should be a valid string [type=string_type, input_value=0, input_type=int]
    For further information visit https://errors.pydantic.dev/2.10/v/string_type
headers.1
  Input should be a valid string [type=string_type, input_value=1, input_type=int]
    For further information visit https://errors.pydantic.dev/2.10/v/string_type
Traceback (most recent call last):
  File "/home/user/app/app.py", line 114, in <module>
    app2 =  gr.Interface(fn = user_greeting2, inputs=inputs2, outputs=outputs2,examples =[[1.0,1.0,0.001, Xhpd,yhpd]])
  File "/usr/local/lib/python3.10/site-packages/gradio/interface.py", line 546, in __init__
    self.render_examples()
  File "/usr/local/lib/python3.10/site-packages/gradio/interface.py", line 904, in render_examples
    self.examples_handler = Examples(
  File "/usr/local/lib/python3.10/site-packages/gradio/helpers.py", line 57, in create_examples
    examples_obj = Examples(
  File "/usr/local/lib/python3.10/site-packages/gradio/helpers.py", line 265, in __init__
    self.dataset = components.Dataset(
  File "/usr/local/lib/python3.10/site-packages/gradio/component_meta.py", line 181, in wrapper
    return fn(self, **kwargs)
  File "/usr/local/lib/python3.10/site-packages/gradio/components/dataset.py", line 118, in __init__
    ex = component.as_example(ex)
  File "/usr/local/lib/python3.10/site-packages/gradio/components/base.py", line 309, in as_example
    return self.process_example(value)
  File "/usr/local/lib/python3.10/site-packages/gradio/components/dataframe.py", line 507, in process_example
    value_df_data = self.postprocess(value)
  File "/usr/local/lib/python3.10/site-packages/gradio/components/dataframe.py", line 431, in postprocess
    return DataframeData(
  File "/usr/local/lib/python3.10/site-packages/pydantic/main.py", line 214, in __init__
    validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)
pydantic_core._pydantic_core.ValidationError: 2 validation errors for DataframeData
headers.0
  Input should be a valid string [type=string_type, input_value=0, input_type=int]
    For further information visit https://errors.pydantic.dev/2.10/v/string_type
headers.1
  Input should be a valid string [type=string_type, input_value=1, input_type=int]
    For further information visit https://errors.pydantic.dev/2.10/v/string_type

System Info

Hugging Face

Severity

Blocking usage of gradio
@caglarari caglarari added the bug Something isn't working label Mar 4, 2025
@abidlabs
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abidlabs commented Mar 4, 2025

Hi @caglarari can you provide a minimal example with correctly formatted code we can use to reproduce the issue? The example provided here is not minimal and not formatted.

@abidlabs abidlabs added the needs repro Awaiting full reproduction label Mar 4, 2025
@caglarari
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Hi,
I added an app.py file (as app.txt). This works fine on my machine with the same configuration given in the added requirements.txt file. It still doesn't work & gives a runtime error on Hugging Face

app.txt.txt

requirements.txt

data_NB.csv

labels_NB.csv

@abidlabs
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abidlabs commented Mar 4, 2025

Hi @caglarari would you please be able to provide a minimal example that we can use to reproduce the issue above? See: https://stackoverflow.com/help/minimal-reproducible-example

@caglarari
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Here

app.txt

data_NB.csv

@abidlabs
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abidlabs commented Mar 9, 2025 •
edited
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Hi @caglarari I just tested on the latest version of Gradio (5.20.1) and the issue is resolved. We previously had an issue where headers needed to be strings but we've sinced fixed this. Please upgrade your local version of Gradio or the sdk_version in your Hugging Face Space.

Image

@abidlabs abidlabs closed this as completed Mar 9, 2025
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