How to Remove Name and Dtype from Pandas Output

How do I remove name and dtype from pandas output

Use the .values attribute.

Example:

s = pd.Series(['race','gender'],index=[1,2])
print(s)
Out[159]:
1      race
2    gender
dtype: object


s.values
array(['race', 'gender'], dtype=object)

You can convert to a list or access each value:

list(s)
['race', 'gender']

python pandas: removing name and dtype in iterrows

You should use the Series.to_string method before printing:

import pandas as pd
import numpy as np

df = pd.DataFrame(np.random.randint(0,10,(3,4)))

for name,s in df.iterrows():
    print(f'row: {name}')
    print(s.to_string())  # to_string outputs only the data, not the metadata

example:

row: 0
0    9
1    0
2    9
3    5
row: 1
0    1
1    2
2    5
3    6
row: 2
0    0
1    1
2    5
3    5

Remove name, dtype from pandas output of dataframe or series

You want just the .values attribute:

In [159]:

s = pd.Series(['race','gender'],index=[311,317])
s
Out[159]:
311      race
317    gender
dtype: object
In [162]:

s.values
Out[162]:
array(['race', 'gender'], dtype=object)

You can convert to a list or access each value:

In [163]:

list(s)
Out[163]:
['race', 'gender']

In [164]:

for val in s:
    print(val)
race
gender

remove dtype info from pandas mode values

Do:

import pandas as pd

# dummy setup
mode_list = ['Race', 'Education', 'Gender', 'Married', 'Housing', 'HH size']
df = pd.DataFrame(data=[['White', 'High School', 'Female', 'Single', 'Rental', 1]], columns=mode_list)

# extract mode
mode_values = df[mode_list].mode().values[0].tolist()
print(mode_values)

Output

['White', 'High School', 'Female', 'Single', 'Rental', 1]

Delete `dtype: object` in pandas DataFrame print

'Address' is the name of the pd.Series and 'Name' is the name of the index

Try:

s.rename_axis(None).rename(None)

Coco Bubble Tea            : 129 E 45th St New York, NY 10017
Gong Cha                   : 75 W 38th St, New York, NY 10018
Smoocha Tea & Juice Bar      : 315 5th Ave New York, NY 10016
dtype: object

Or I'd rewrite your function

def boba_recs(lat, lng):
    f1 = pd.read_csv("./boba_final.csv") 
    user_loc = Point(lng, lat) # converts user lat/long to point object
    # makes dataframe of distances between each boba place and the user loc
    f1['Distance'] = [user_loc.distance(Point(xy)) for xy in zip(f1.Longitude, f1.Lat)]
    # grabs the three smallest distances
    boba = f1.nsmallest(3, 'Distance').set_index('Name') # sets index to name
    return(": " + boba['Address']).rename_axis(None).rename(None)

If you want a string

def boba_recs(lat, lng):
    f1 = pd.read_csv("./boba_final.csv") 
    user_loc = Point(lng, lat) # converts user lat/long to point object
    # makes dataframe of distances between each boba place and the user loc
    f1['Distance'] = [user_loc.distance(Point(xy)) for xy in zip(f1.Longitude, f1.Lat)]
    # grabs the three smallest distances
    boba = f1.nsmallest(3, 'Distance').set_index('Name') # sets index to name
    temp = (": " + boba['Address']).rename_axis(None).__repr__()
    return temp.rsplit('\n', 1)[0]

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