Pandas: str.split()

How to use split expand=True to expand records in a cell to multi columns and limit it with n parameter.¶

In [5]:

import pandas as pd
df = pd.read_csv("str_split_expand_true.csv")
df

Out[5]:

	name	email
0	john,doe j	jdj@dell.com
1	mary,ann d	mad@apple.com
2	baku,raju b	brj@microsoft.com

In [38]:

df["name"].str.split(",", expand=True)

Out[38]:

	0	1
0	john	doe j
1	mary	ann d
2	baku	raju b

assign it back to the dataframe¶

In [35]:

df[["First Name", "Last Name"]]  =  df["name"].str.split(",", expand=True)
df

Out[35]:

	name	email	First Name	Last Name
0	john,doe j	jdj@dell.com	john	doe j
1	mary,ann d	mad@apple.com	mary	ann d
2	baku,raju b	brj@microsoft.com	baku	raju b

drop off redundant original column¶

In [34]:

df.drop("name" , axis="columns")

Out[34]:

	email	First Name	Last Name
0	jdj@dell.com	john	doe j
1	mad@apple.com	mary	ann d
2	brj@microsoft.com	baku	raju b

a lot of things can be done after this point.. nunique, value_counts, catergory¶

In [60]:

df = pd.read_csv("str_split_expand_true.csv")
df[["fname","lname"]] = df["name"].str.split(",", expand=True)
df[["lname","minit"]] = df["lname"].str.split(" ", expand=True)
df["fname"].value_counts()

Out[60]:

baku    1
mary    1
john    1
Name: fname, dtype: int64

In [61]:

df["fname"].nunique()

Out[61]:

3

In [68]:

import pandas as pd
df = pd.read_csv("str_split_expand_true.csv")
df["name"].str.split(",").get(0)

Out[68]:

['john', 'doe j']

In [ ]: