Is there a way to find when a cell in a row changes compared to another dataframe?

Question

I'm looking to compare two dataframes and find where they differ in Python. This wont be restricted to duplications either, and will also involve identifying new entries and adding the date of this change. For example:

df1 =

df2 =

df3 =

Please let me know if you need anymore detail, thank you.

Answer 1

With the dataframes you provided:

import pandas as pd

df1 = pd.DataFrame(
    {
        "item": ["bannana", "orange", "hammer"],
        "size": [10, 5, 25],
        "colour": ["yellow", "orange", "wood"],
    }
)

df2 = pd.DataFrame(
    {
        "item": ["bannana", "orange", "snake", "hammer"],
        "size": [12, 5, 55, 25],
        "colour": ["yellow", "green", "green", "wood"],
    }
)

Here is one way to do it:

TODAY = pd.Timestamp.today().strftime("%d/%m/%Y")

# Merge dataframes
df3 = pd.merge(
    left=df2, right=df1, how="left", on="item", suffixes=["_new", "_old"]
).fillna("")

# Add new empty columns
df3["date_size_changed"] = ""
df3["date_colour_changed"] = ""

# Sort columns
df3 = df3.reindex(
    columns=[
        "item",
        "size_new",
        "size_old",
        "date_size_changed",
        "colour_new",
        "colour_old",
        "date_colour_changed",
    ]
)

# Compare values and add TODAY when different
for col in ["size", "colour"]:
    df3[f"date_{col}_changed"] = df3.apply(
        lambda x: TODAY
        if x[f"{col}_new"] != x[f"{col}_old"] and x[f"{col}_old"] != ""
        else "",
        axis=1,
    )

print(df3)
# Output
      item  size_new size_old date_size_changed colour_new colour_old  \
0  bannana        12     10.0        18/09/2022     yellow     yellow   
1   orange         5      5.0                        green     orange   
2    snake        55                                 green
3   hammer        25     25.0                         wood       wood   

  date_colour_changed  
0
1          18/09/2022  
2
3

Answer 2

This is not possible, very sorry