CODEWITHSUNDEEP
pythonpandas
Lucy
Lucy

Reputation: 401

Create multiple dataframe using for loop in python 2.7

I have a list of locations 

["HOME", "Office", "SHOPPING"]

and a pandas data frame "DF"

Start_Location  End_Location    Date
OFFICE          HOME            3-Apr-15
OFFICE          HOME            3-Apr-15
HOME            SHOPPING    3-Apr-15
HOME            SHOPPING    4-Apr-15
HOME            SHOPPING    4-Apr-15
SHOPPING    HOME            5-Apr-15
SHOPPING    HOME            5-Apr-15
HOME            SHOPPING    5-Apr-15

I want to create 3 different data frames for HOME, Office, SHOPPING using for loop, but I am not able to do it.

I am new to python

Please help.

Thanks lucy

Upvotes: 0

Views: 4536

Answers (3)

Luis Fernando Larota
Luis Fernando Larota

Reputation: 1

You could probably have a dictionary and you want to convert it to some dataframes, based on the keys of your dictionary:

gbl = globals()
for keys, values in dictionary.items():
   gbl['df_min'+ str(keys)] = pd.DataFrame(values)

Upvotes: 0

HYRY
HYRY

Reputation: 97331

Use groupby() and then call it's get_group() method:

import pandas as pd
import io

text = b"""Start_Location  End_Location    Date
OFFICE          HOME            3-Apr-15
OFFICE          HOME            3-Apr-15
HOME            SHOPPING    3-Apr-15
HOME            SHOPPING    4-Apr-15
HOME            SHOPPING    4-Apr-15
SHOPPING    HOME            5-Apr-15
SHOPPING    HOME            5-Apr-15
HOME            SHOPPING    5-Apr-15"""

locations = ["HOME", "OFFICE", "SHOPPING"]

df = pd.read_csv(io.BytesIO(text), delim_whitespace=True)
g = df.groupby("Start_Location")
for name, df2 in g:
    globals()["df_" + name.lower()] = df2

but I think add global variables in a for loop isn't a good method, you can convert the groupby to a dict by:

d = dict(iter(g))

then you can use d["HOME"] to get the data.

Upvotes: 1

Lucy
Lucy

Reputation: 401

I got the answer which I was looking for 

import pandas as pd
gbl = globals()
for i in locations:
gbl['df_'+i] = df[df.Start_Location==i]

This will create 3 data frames df_HOME, df_office and df_SHOPPING

Thanks,

Upvotes: 5

Related Questions