[Python] Python - Add Missing Data to New Dataframe

I am comparing two dataframes by looping through both and determining if data (row) from one does not exist in the other. If there is no match, I want to add that specific row to a third dataframe. I was able to achieve this with the append() method, but Python warns me that it is deprecated and tells me to use concat instead. Unfortunately, I cannot get concat to achieve the same result.

import pandas as pd

df1 = pd.DataFrame(
{
"Animal": ["Corgi",
"Labrador",
"Orange Cat",
"Black Cat"],
"Owner": ["Bob",
"Joe",
"Sara",
"Glen"]
})

df2 = pd.DataFrame(
{
"Animal": ["Corgi",
"Labrador",
"Black Cat"],
"Owner": ["Bob",
"Joe",
"Glen"]
})

dfF = pd.DataFrame(columns=["Animal", "Owner"])

df1Sort = df1.sort_values(by=["Animal"]).reset_index(drop=True)
df2Sort = df2.sort_values(by=["Animal"]).reset_index(drop=True)

for ind in df1Sort.index:
for subInd in df2Sort.index:
if df1Sort["Animal"][ind] == df2Sort["Animal"][subInd]:
print("Found match:",
df1Sort["Animal"][ind],
"-",
df1Sort["Owner"][ind])
break
elif df2Sort.index[subInd] == df2Sort.index[-1]:
print("No match for:",
df1Sort["Animal"][ind],
"-",
df1Sort["Owner"][ind])
dfF = pd.concat([dfF, df1Sort.iloc[ind]], axis=0, ignore_index=True)
break

print(dfF)

The output is:

• Found match: Black Cat - Glen
• Found match: Corgi - Bob
• Found match: Labrador - Joe
• No match for: Orange Cat - Sara
• Animal Owner 0
• 0 NaN NaN Orange Cat
• 1 NaN NaN Sara

I would like the new dataframe to read as such:

• Animal Owner
• 0 Orange Cat Sara

How do I alter the concat line to achieve this?

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