我正在尝试将json文件从github导入到Google colab。它可以工作,但不能从文件中读取所有列。这是我的代码:
import pandas as pd
url = 'https://raw.githubusercontent.com/lequanngo/WorldHappiness/master/WorldHappiness.json'
df = pd.read_json(url, orient='columns')
df.head(10)
这是结果:
country||ladder||ladderSD||Positive_affect||Negative_affect||SocialSupport||Freedom
Finland| |1| |4| |41| |10| |2| |5|
Denmark
Norway
etc
',country,ladder,ladder_sd,positive_affect,negative_affect,social_support,freedom,corruption,generosity,gdp_per_capita,healthy_life_expectancy,continent\n0,Finland,1,4,41,10,2,5,4,47,22,27,Europe\n1'
显示所有11列(国家,阶梯,阶梯SD,positve_affect,negative_affect等)。但是当我通过使用
获得描述性统计数据时df.describe()
|ladder| |ladderSD|
count 156 156
mean 78.5 78.5
std
min
25%
仅计算梯形图和梯形图SD。不考虑positive_affect和negative_affect以及其他所有连续数据列。
有人可以帮我吗?
答案 0 :(得分:0)
这是您期望的输出吗?
>>> url = 'https://raw.githubusercontent.com/lequanngo/WorldHappiness/master/WorldHappiness.json'
>>> df = pd.read_json(url, orient='records', dtype='dict')
>>> df.head()
Country (region) Ladder SD of Ladder Positive affect Negative affect ... Freedom Corruption Generosity Log of GDP\nper capita Healthy life\nexpectancy
0 Finland 1 4 41 10 ... 5 4 47 22 27
1 Denmark 2 13 24 26 ... 6 3 22 14 23
2 Norway 3 8 16 29 ... 3 8 11 7 12
3 Iceland 4 9 3 3 ... 7 45 3 15 13
4 Netherlands 5 1 12 25 ... 19 12 7 12 18
[5 rows x 11 columns]
>>> df.describe()
Ladder SD of Ladder
count 156.000000 156.000000
mean 78.500000 78.500000
std 45.177428 45.177428
min 1.000000 1.000000
25% 39.750000 39.750000
50% 78.500000 78.500000
75% 117.250000 117.250000
max 156.000000 156.000000
>>> df.describe(include='all')
Country (region) Ladder SD of Ladder Positive affect Negative affect ... Freedom Corruption Generosity Log of GDP\nper capita Healthy life\nexpectancy
count 156 156.000000 156.000000 156.0 156.0 ... 156.0 156 156.0 156 156
unique 156 NaN NaN 156.0 156.0 ... 156.0 149 156.0 153 151
top Nepal NaN NaN 155.0 155.0 ... 155.0 155.0
freq 1 NaN NaN 1.0 1.0 ... 1.0 8 1.0 4 6
mean NaN 78.500000 78.500000 NaN NaN ... NaN NaN NaN NaN NaN
std NaN 45.177428 45.177428 NaN NaN ... NaN NaN NaN NaN NaN
min NaN 1.000000 1.000000 NaN NaN ... NaN NaN NaN NaN NaN
25% NaN 39.750000 39.750000 NaN NaN ... NaN NaN NaN NaN NaN
50% NaN 78.500000 78.500000 NaN NaN ... NaN NaN NaN NaN NaN
75% NaN 117.250000 117.250000 NaN NaN ... NaN NaN NaN NaN NaN
max NaN 156.000000 156.000000 NaN NaN ... NaN NaN NaN NaN NaN
[11 rows x 11 columns]