I am trying to merge data frames by looping since each loop merges the data frames based on a different column.
The following is what I have so far:
f1 = pd.DataFrame({"color": ["blue", "yellow", "red"],
"abbv": ["b", "y", "r"]})
df2 = pd.DataFrame({"color_1": ["blue", "red", "yellow"],
"color_2": ["yellow", "blue", "red"],
"total": ["green", "purple", "orange"]})
drop_column = df1.columns.tolist()
drop_column.remove("abbv")
co = "color"
dd4 = []
for i in [1,2]:
dd3 = pd.merge(df2,df1,
left_on = f"{co}_{i}",
right_on = "color",
how="left")
dd3 = dd3.rename(columns={"abbv":f"abbv_{i}"}).drop(drop_column, axis=1)
dd4.append(dd3)
print(dd4)
This is the output:
[ color_1 color_2 total abbv_1
0 blue yellow green b
1 red blue purple r
2 yellow red orange y, color_1 color_2 total abbv_2
0 blue yellow green y
1 red blue purple b
2 yellow red orange r]
What I am trying to achieve:
color_1 | color_2 | total | abbv_1 | abbv_2 |
---|---|---|---|---|
blue | yellow | green | b | y |
. | . | . | . | . |
. | . | . | . | . |
If I understand your question right, you want to use .map
:
m = df1.set_index("color")["abbv"]
df2["abbv_1"] = df2["color_1"].map(m)
df2["abbv_2"] = df2["color_2"].map(m)
print(df2)
Prints:
color_1 color_2 total abbv_1 abbv_2
0 blue yellow green b y
1 red blue purple r b
2 yellow red orange y r
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