如何使用列数据对大数据进行统计分析
如何使用列数据对大数据进行统计分析
提问于 2019-08-21 06:15:34
在我的数据集中，我有48000个村庄，每个村庄有10到12种作物，每个村庄的作物播种面积是多少，我想知道哪种作物的主要区域是哪个村庄，在所有作物中，1到.的比例是多少？在那个村庄里种庄稼。也就是说，我想找出村级作物的比例，如果A村有作物-1和作物-2，那么A占作物-1和作物-2的百分比是多少？
因此，接下来，我可以根据特定的crop.so对村庄进行排序，然后我可以了解哪个作物是大面积种植给哪个村庄的。
District Taluka Village Name Crop Area in hec
0 Ahmednagar Pathardi Alhanwadi Bajara 370.0
1 Ahmednagar Pathardi Adgaon Bajara 302.0
2 Ahmednagar Pathardi Ambika Nagar Bajara 40.0
3 Ahmednagar Pathardi Bharajwadi Bajara 90.0
4 Ahmednagar Pathardi Bhalgaon Bajara 254.0
5 Ahmednagar Pathardi Bhawarwadi (N.V.) Bajara 35.0
6 Ahmednagar Pathardi Badewadi Bajara 17.0
7 Ahmednagar Pathardi Akola Bajara 175.0
8 Ahmednagar Pathardi Auranjpur Bajara 35.0
9 Ahmednagar Pathardi Agaskhand Bajara 100.0
10 Ahmednagar Pathardi Alhanwadi Cotton 150.0
11 Ahmednagar Pathardi Adgaon Cotton 310.0
12 Ahmednagar Pathardi Ambika Nagar Cotton 131.0
13 Ahmednagar Pathardi Bharajwadi Cotton 161.0
14 Ahmednagar Pathardi Bhalgaon Cotton 562.0
15 Ahmednagar Pathardi Bhawarwadi (N.V.) Cotton 211.0
16 Ahmednagar Pathardi Badewadi Cotton 104.0
17 Ahmednagar Pathardi Akola Cotton 550.0
18 Ahmednagar Pathardi Auranjpur Cotton 0.0
19 Ahmednagar Pathardi Agaskhand Cotton 0.0
20 Ahmednagar Pathardi Alhanwadi Soybean 26.0
21 Ahmednagar Pathardi Adgaon Soybean 52.0
22 Ahmednagar Pathardi Ambika Nagar Soybean 72.0
23 Ahmednagar Pathardi Bharajwadi Soybean 88.0
24 Ahmednagar Pathardi Bhalgaon Soybean 90.0
25 Ahmednagar Pathardi Bhawarwadi (N.V.) Soybean 93.0
26 Ahmednagar Pathardi Badewadi Soybean 100.0
27 Ahmednagar Pathardi Akola Soybean 10.0
28 Ahmednagar Pathardi Auranjpur Soybean 45.0
29 Ahmednagar Pathardi Agaskhand Soybean 20.0
30 Ahmednagar Pathardi Alhanwadi Maize 10.0
31 Ahmednagar Pathardi Adgaon Maize 1.5
32 Ahmednagar Pathardi Ambika Nagar Maize 3.0
33 Ahmednagar Pathardi Bharajwadi Maize 5.0
34 Ahmednagar Pathardi Bhalgaon Maize 12.0
35 Ahmednagar Pathardi Bhawarwadi (N.V.) Maize 51.0
36 Ahmednagar Pathardi Badewadi Maize 5.0
37 Ahmednagar Pathardi Akola Maize 25.0
38 Ahmednagar Pathardi Auranjpur Maize 5.0
39 Ahmednagar Pathardi Agaskhand Maize 10.0import pandas as pd
import numpy as np
D=pd.read_excel("/media/desktop/Sample-2.xlsx","Sheet1")
village=D["Village Name"].unique()
crop=D["Crop"].unique()
q1=[]
for i in village:
for j in crop:
a=D["Village Name"]==i
b=D["Crop"]==j
D1=D[a&b]
q1.append(D1)
q2=[]
for i in q1:
if i.empty==False:
q2.append(i)现在我们可以得到村庄的作物播种面积，接下来我们必须计算A村的作物-1，%的作物-2.%的作物-N。
公式:对于A村的作物-1是作物-1/在那个村庄的所有作物，我们得到的作物-1%在那个村庄，同样的方法是找出%的作物-2。
所有村庄都一样。
有什么建议吗？
回答 3
Stack Overflow用户
回答已采纳
发布于 2019-08-21 06:29:16
第一次用于每个村庄的最高作物：
df1 = df.sort_values(['Village Name','Area in hec'], ascending=[True, False])
df2 = df1.drop_duplicates('Village Name')
print (df2)
District Taluka Village Name Crop Area in hec
11 Ahmednagar Pathardi Adgaon Cotton 310.0
9 Ahmednagar Pathardi Agaskhand Bajara 100.0
17 Ahmednagar Pathardi Akola Cotton 550.0
0 Ahmednagar Pathardi Alhanwadi Bajara 370.0
12 Ahmednagar Pathardi Ambika Nagar Cotton 131.0
28 Ahmednagar Pathardi Auranjpur Soybean 45.0
16 Ahmednagar Pathardi Badewadi Cotton 104.0
14 Ahmednagar Pathardi Bhalgaon Cotton 562.0
13 Ahmednagar Pathardi Bharajwadi Cotton 161.0
15 Ahmednagar Pathardi Bhawarwadi (N.V.) Cotton 211.0和每种作物的面积百分比：
s = df1.groupby("Crop")['Area in hec'].transform('sum')
df1['perc'] = df1['Area in hec'].div(s).mul(100)
print (df1.head(10))
District Taluka Village Name Crop Area in hec perc
11 Ahmednagar Pathardi Adgaon Cotton 310.0 14.226709
1 Ahmednagar Pathardi Adgaon Bajara 302.0 21.297602
21 Ahmednagar Pathardi Adgaon Soybean 52.0 8.724832
31 Ahmednagar Pathardi Adgaon Maize 1.5 1.176471
9 Ahmednagar Pathardi Agaskhand Bajara 100.0 7.052186
29 Ahmednagar Pathardi Agaskhand Soybean 20.0 3.355705
39 Ahmednagar Pathardi Agaskhand Maize 10.0 7.843137
19 Ahmednagar Pathardi Agaskhand Cotton 0.0 0.000000
17 Ahmednagar Pathardi Akola Cotton 550.0 25.240936
7 Ahmednagar Pathardi Akola Bajara 175.0 12.341326Stack Overflow用户
发布于 2019-08-21 06:24:43
首先使用groupby将每个城市的面积之和合计成一个总数
total_lands = D.groupby(["Village Name"])['Area in hec'].agg(['sum']).drop_index()然后按城市和作物分组，得到每个城市每一作物的总量。
lands_by_crop = D.groupby(["Village Name","Crop"])['Area in hec'].agg(['sum'])最后计算百分比..。
percentages = lands_by_crop.map(lambda x:x/total_lands[x.index["Village Name"]])我认为应该有效(不完全确定在最后一步).也许有更有效的方法来解决这个问题，我不确定
Stack Overflow用户
发布于 2019-08-21 06:30:36
要了解农作物的数量-村庄智慧，请使用以下方法：
D.filter(items = ["VillageName","Crop", "Area"],axis=1).groupby(by = ["VillageName","Crop"])然后，你可以除以sumTotal的作物面积(D.filter(项目=“作物”，“区域”，axis=1).groupby(由=“作物”)或sumTotal村地区(D.filter(项目= "VillageName"，“区域”，axis=1).groupby(由=“VillageName”))得出的比例。
页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/57585469
复制相关文章
相似问题
腾讯云开发者
