So, my expectation is one single table with the same content as the df appears on my dashboard. However, three tables with slightly different contents appear on the dashboard as shown below:
[First and second tables]
The expected table actually appears as the first table, but the second table does not have score element and the third table’s labels are followed by .1 and no values appear.
I do not have any ideas what is the cause of this behaviour. Do anybody experienced something similar, or have a solution to prevent wandb from putting the second and third tables on the dashboard?
Hey Atsushi:
I used the code you shared but not seeing the same problem you have. I’m wondering if the problem is coming from your version of pandas or your code somewhere else accidentally logging the tables you are seeing.
Here’s the code I used with small modification of your code
import pandas as pd# Define the data as a dictionarydata = { 'run_name': ['global_gt'], 'total_mass': [5.582391], 'mx': [-0.002781], 'my': [-0.008022], 'mz': [0.001889], 'ixx': [0.193884], 'iyy': [0.201152], 'izz': [0.198709], 'ixy': [0.000203], 'iyz': [0.000165], 'izx': [0.000203], 'score': [0.0], 'num_active_vxs': [19191]}# Create the DataFramedf = pd.DataFrame(data)# Display the DataFrameprint(df)run_name = df['run_name'].iloc[0]wandb.init( entity="myentity", project="dfLog",)dropped_dataser = df.drop(columns=['run_name', 'score']).iloc[0]# dropped_dataser.index= tagged_columnsfor step in range(1, 5): wandb.log(data=dropped_dataser.to_dict(), step=step)to_log = wandb.Table(dataframe=df)wandb.log({"result": to_log}) # columns=list(columns), data=[data])})wandb.finish()
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