Use a dictionary to replace values within a dataframe column

Question

I have a dataframe column of strings. Now I want to replace specific words in these strings with a value from another dataframe which has the meaning of the word to be replaced. I am currently using iterrrows() which takes about 2 minutes for 25000 rows. I would like to know if there is a more efficient way of doing this.

syn = pd.ExcelFile("C:/Key-Value.xlsx")
df_syn = syn.parse("Keys")

for idx, row in df_syn.iterrows():  
    df['col'] = df['col'].str.replace(r"\b"+row['synonym']+r"\b", row['word'])

piRSquared · Accepted Answer · 2017-11-11 00:04:20Z

1

IIUC:

Setup

df_syn = pd.DataFrame(dict(synonym=['hug', 'kiss'], word=['warm', 'tender']))
df = pd.DataFrame(dict(col=['I want a hug', 'a kiss would be great']))

print(df_syn, df, sep='\n\n')

  synonym    word
0     hug    warm
1    kiss  tender

                     col
0           I want a hug
1  a kiss would be great

Solution

mapping = df_syn.assign(
    synonym=df_syn.synonym.radd(r'\b').add(r'\b')
).set_index('synonym').word.to_dict()

df.replace({'col': mapping}, regex=True)

                       col
0            I want a warm
1  a tender would be great

answered Nov 11, 2017 at 0:04

piRSquared

296k68 gold badges509 silver badges654 bronze badges

Sign up to request clarification or add additional context in comments.

Collectives™ on Stack Overflow

Use a dictionary to replace values within a dataframe column

1 Answer 1

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

Comments

Your Answer

Sign up or log in

Post as a guest

Related