在 pandas DataFrame打印中删除`dtype:object` [英] Delete `dtype: object` in pandas DataFrame print

问题描述

这是我的代码:

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'])

这将返回:

Name
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
Name: Address, dtype: object

几乎完美，除了我想摆脱名称:地址，dtype:对象"行.我已经尝试了几件事，而且不会弄乱其他所有内容的格式就不会消失.

Almost perfect except I want to get rid of the "Name: Address, dtype: object" row. I've tried a few things and it just won't go away without messing up the format of everything else.

推荐答案

'Address'是pd.Series的名称，而'Name'是索引的名称

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

尝试:

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

或者我会重写您的函数

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)

如果您想要一个字符串

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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