Python: Convert dataframe into a list with string items inside list
Question:
I currently have code that reads in an Excel table (image below):
# Read in zipcode input file
us_zips = pd.read_excel("Zipcode.xls")
us_zips
I use the following code to convert the dataframe zip codes into a list:
us_zips = list(us_zips.values.flatten())
When I print us_zips it looks like this:
[10601, 60047, 50301, 10606]
…but I want it to look like this [“10601”, “60047”, “50301”, “10606”]
How can I do that? *Any help is greatly appreciated
Answers:
You can just cast the column dtype using astype(str) and then convert to list using .values.tolist(), this returns a numpy array using .values which has a member function to convert this to a list:
In [321]:
us_zips['zipcode'].astype(str).values.tolist()
Out[321]:
['10601', '60047', '50301', '10606']
It worked for me without .values():
list = df[col_name].astype(str).tolist()
After creating your list you can simply do the following to convert all your list elements to strings:
us_zips = [str(i) for i in us_zips]
Complete code:
df = pd.DataFrame()
df["x"] = [10601, 60047, 50301, 10606]
us_zips = list(df["x"].values.flatten())
print(us_zips)
us_zips = [str(i) for i in us_zips]
print(us_zips)
Results:
[10601, 60047, 50301, 10606]
['10601', '60047', '50301', '10606']
I currently have code that reads in an Excel table (image below):
# Read in zipcode input file
us_zips = pd.read_excel("Zipcode.xls")
us_zips
I use the following code to convert the dataframe zip codes into a list:
us_zips = list(us_zips.values.flatten())
When I print us_zips it looks like this:
[10601, 60047, 50301, 10606]
…but I want it to look like this [“10601”, “60047”, “50301”, “10606”]
How can I do that? *Any help is greatly appreciated
You can just cast the column dtype using astype(str) and then convert to list using .values.tolist(), this returns a numpy array using .values which has a member function to convert this to a list:
In [321]:
us_zips['zipcode'].astype(str).values.tolist()
Out[321]:
['10601', '60047', '50301', '10606']
It worked for me without .values():
list = df[col_name].astype(str).tolist()
After creating your list you can simply do the following to convert all your list elements to strings:
us_zips = [str(i) for i in us_zips]
Complete code:
df = pd.DataFrame()
df["x"] = [10601, 60047, 50301, 10606]
us_zips = list(df["x"].values.flatten())
print(us_zips)
us_zips = [str(i) for i in us_zips]
print(us_zips)
Results:
[10601, 60047, 50301, 10606]
['10601', '60047', '50301', '10606']