CODEWITHSUNDEEP
pythondataframe
user8560167
user8560167

Reputation:

comparing lenght of specific column rows in dataframe, python

Input:

DF1:
name, message
adam, hello, i'am
viola, hi, my name is

data:
name, message
adam, hello, i'am
viola, hi, my name

I want to compare, if length of messages for specific name (for example: adam and adam) are same pass, else print this row.

Code:

if df['message'].apply(lambda x: len(x)) == data['name'].apply(lambda x: len(x)):
    pass
else:
    df['message'].apply(lambda x: print(x)) 
    #edit: i can use maybe df.loc[:,'message'] as well i think

But I am receiving: TypeError: object of type 'float' has no len(), why?

Upvotes: 1

Views: 48

Answers (2)

sg.sysel
sg.sysel

Reputation: 163

There might be a better way, but this could work for you:

import pandas
dt = pandas.DataFrame([["Adam","Hello, I am Adam"], ["Viola", "How are you"]], columns=["name", "message"])
data = pandas.DataFrame([["Adam","Hello, I am Adam"], ["Viola", "How are ya"]], columns=["name", "message"])

print(dt)
print(data)

data.columns = ["name", "message_data"]

merged = dt.merge(data, on=["name"])
merged[merged.message.str.len() != merged.message_data.str.len()]

First, you need to rename the ["message"] column, so that it doesn't clash in the merge. Then you merge both dataframes, keeping only names which exist in both dataframes. Finaly, you compare the lengths of the strings in ["message"] with those in ["message_data"] and use that to extract those rows of the merged table that are different.

If you specifically want only the message, you can do:

merged.loc[merged.message.str.len() != merged.message_data.str.len(), "message"]

Printing the result line-by-line should be straightforward.

Upvotes: 1

Bigya Pradhan
Bigya Pradhan

Reputation: 206

A better approach would be to merge the two dataframes based on the name.

import pandas as pd
#construct df1
#construct df2

#merge two df based on name
df=pd.merge(df1,df2,on="name")

#get the length of messages and filter out unequal length

df_same_length=df[~df["message_x"].astype(str).str.len()==df["message_y"].astype(str).str.len()]

print(df_same_length["name"])

Upvotes: 1

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