Mapping data from one table to other using loop

Question

I have a dataframe DF1, that has 4 distinct one word named columns, and one identifier column, tz:

Tz, Population, Citibike, Residential, Taxi

Initially, I want to create a dictionary preserving the elements index:

for name in len(DF1.columns):
    name = {tz:DF1.name[tz] for tz in DF1.index}

But this produces error either of int object not iterable if I put len(SMdata.columns) or that Dataframe has no object name if I remove the len function from the for loop.

I also have another data frame DF2, to which I am trying to add columns from the first dataframe but most importantly using mapping function on it's column "LocationID".

To do this I tried writing this code:

for name in list(DF1.columns):
    Key = name
    DF2[name] = DF2.LocationID.map(key)

However, I keep running into "TypeError: 'str' object is not callable"

I am confused as to why is this approach not working!

EDIT: Is it possible to create a loop for getting entries from a column, performing math operation on all values, and adding new val into new column. Basically a loop application for this code:

Df["log_column_name"] = np.log[Df[column_name]]

Which line is the line where this problem is happening? It's best if you provide some more code. — Enthus3d, Sep 21 '19 at 22:38
Updated the problem. My concern is that I want to basically merge two tables, using LocationID column in DF2. I don't want to use the .merge function, but create a dictionary from DF1 columns, then use the .map function to merge with DF2 — pratik watwani, Sep 21 '19 at 23:19
use dict could be an option but this could do more easy.. can you show a example of df1 and df2 and your expected output? — ansev, Sep 21 '19 at 23:22
yes, or an example. I need an inputs dataframe and output dataframe — ansev, Sep 21 '19 at 23:45

Enthus3d · Accepted Answer · 2019-09-21T23:25:21.483

1

For the first problem on line

for name in len(DF1.columns):

You are trying to have the for loop loop through len(DF1.columns), but len() functions in Python return integers. You may have wanted instead to loop through the DF1.columns itself:

for name in DF1.columns:

For the second problem, it's likely that somewhere in your code, you make a call that is similar to this,

str = ../

The error is complaining that str is an object in python that is not callable, so make sure you do not use any variables named 'str' (because str is a special name in Python).

Referenced from the question here

edited Sep 21 '19 at 23:25

answered Sep 21 '19 at 22:43

Enthus3d

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What about the first part of the problem? Can you suggest something wrt that, cause I cannot seem to get it running! – pratik watwani Sep 21 '19 at 22:44
Oh, my bad. I only glossed over the first part. I'll take a closer look now. – Enthus3d Sep 21 '19 at 22:45
@pratikwatwani I think you are trying to use a for loop on the length, which is an integer. You will need to give the for loop some lists or something with an iterator to loop on instead. – Enthus3d Sep 21 '19 at 22:47
I mentioned in my problem, that even when I remove the len function, there is no presence of the dictionary that I used the loop to create! – pratik watwani Sep 21 '19 at 22:57
hmm. But you are not using the loop to create a dictionary, you are setting DF2 with [name] as its index in your second piece of code. – Enthus3d Sep 21 '19 at 23:10
1

`for name in list(DF1.columns):` this isn't necessary, only you need `for name in df.columns` – ansev Sep 21 '19 at 23:19
Understood. Thanks for letting me know :). – Enthus3d Sep 21 '19 at 23:24

ansev · Answer 2 · 2019-09-21T23:16:11.747

for name in len(DF1.columns):

This only is execute one time because len() return one value... then you need for name in df.columns... but is better use DataFrame.to_dict whit DataFrame.transpose. You don't need a for loop. Pandas provided methods to it.

Example:

import pandas as pd
import numpy as np
df=pd.DataFrame()
df['col1']='a b c d e f'.split()
df['col2']=[1,2,3,4,5,6]
df['col3']=[32,21,'h',2,6,10]
print(df)
rows_dict=df.T.to_dict('list')
print(rows_dict)



  col1  col2 col3
0    a     1   32
1    b     2   21
2    c     3    h
3    d     4    2
4    e     5    6
5    f     6   10
{0: ['a', 1, 32], 1: ['b', 2, 21], 2: ['c', 3, 'h'], 3: ['d', 4, 2], 4: ['e', 5, 6], 5: ['f', 6, 10]}

Problem 2

for name in list(DF1.columns):
    DF2[name] = DF2.LocationID.map(key)

in any case you would be adding df2 data to other df2 columns, but you are never using df1 data ... please provide an example of what you want to do exactly

Mapping data from one table to other using loop

2 Answers2