Как найти соседние значения в фрейме данных с заданными значениями x и y?

С предоставленным вами кадром данных:

import pandas as pd

df = pd.DataFrame(
    {
        "x": [0, 1, 2, 3, 0, 1, 2, 3],
        "y": [0, 0, 0, 0, 1, 1, 1, 1],
        "value": ["red", "pink", "green", "blue", "yellow", "orange", "blue", "purple"],
    }
)

Вот один из способов:

# Find adjacent values
for i, t in enumerate([(-1, 0), (0, -1), (1, 0), (0, 1)]):
    df[f"adjacent_{i}"] = df.apply(
        lambda df_: df.loc[
            (df["x"] == df_["x"] + t[0]) & (df["y"] == df_["y"] + t[1]), "value"
        ].values,
        axis=1,
    )

# Get values and add them to a list in temporary column
for col in df.columns:
    if not col.startswith("adjacent"):
        continue
    df[col] = df[col].map(lambda x: x[0] + "," if x.size > 0 else pd.NA)

df["temp"] = (
    df[[f"adjacent_{i}" for i in range(4)]].fillna("").sum(axis=1).str.split(",")
)

# Reorder dataframe to move nan values to the most right
df = (
    pd.DataFrame(
        df["temp"].values.tolist(), index=df.set_index(["x", "y", "value"]).index
    )
    .add_prefix("adjacent_")
    .replace("", pd.NA)
    .dropna(how = "all", axis=1)
    .reset_index()
)

# Rename columns
df.columns = ["x", "y", "value"] + [f"adjacent_{i+1}" for i in range(3)]

Затем:

print(df)
# Output
   x  y   value adjacent_1 adjacent_2 adjacent_3
0  0  0     red       pink     yellow       <NA>
1  1  0    pink        red      green     orange
2  2  0   green       pink       blue       blue
3  3  0    blue      green     purple       <NA>
4  0  1  yellow        red     orange       <NA>
5  1  1  orange     yellow       pink       blue
6  2  1    blue     orange      green     purple
7  3  1  purple       blue       blue       <NA>