如何在Python中从OSM文件中提取和可视化数据

我在我的桌面上下载了一个OpenStreetMap文件，并在jupyter笔记本中使用了我的OSM文件

我的代码：

import xml.etree.cElementTree as ET
osm_file = "ahmedabad_india.osm"

for event, elem in ET.iterparse(osm_file, events=("start",)):
     print(elem)
     # prints the Element 'osm' at 0x03A7DC08>
     #<Element 'bounds' at 0x03A7DDA0>
     #<Element 'node' at 0x03A7DE90>
     #<Element 'tag' at 0x03A7DF08> and so on ...

import osmium as osm
import pandas as pd

class OSMHandler(osm.SimpleHandler):
    def __init__(self):
        osm.SimpleHandler.__init__(self)
        self.osm_data = []

    def tag_inventory(self, elem, elem_type):
        for tag in elem.tags:
            self.osm_data.append([elem_type, 
                                   elem.id, 
                                   elem.version,
                                   elem.visible,
                                   pd.Timestamp(elem.timestamp),
                                   elem.uid,
                                   elem.user,
                                   elem.changeset,
                                   len(elem.tags),
                                   tag.k, 
                                   tag.v])

    def node(self, n):
        self.tag_inventory(n, "node")

    def way(self, w):
        self.tag_inventory(w, "way")

    def relation(self, r):
        self.tag_inventory(r, "relation")


osmhandler = OSMHandler()
# scan the input file and fills the handler list accordingly
osmhandler.apply_file("muenchen.osm")

# transform the list into a pandas DataFrame
data_colnames = ['type', 'id', 'version', 'visible', 'ts', 'uid',
                 'user', 'chgset', 'ntags', 'tagkey', 'tagvalue']
df_osm = pd.DataFrame(osmhandler.osm_data, columns=data_colnames)
df_osm = tag_genome.sort_values(by=['type', 'id', 'ts'])

将xml.etree.cElementTree作为ET导入
osm_file=“ahmedabad_india.osm”
对于事件，ET.iterparse（osm_文件，事件=（“开始”），中的元素：
打印（elem）
#在0x03A7DC08处打印元素“osm”>
#
#
#等等。。。

我想查看所有

标签的内容，即。
等等

我尝试使用
elem
标记，但它不打印任何内容

可以帮助我找出，谁得到标签的内容，比如节点、方法等等？< /P> < P>你可以从<代码> .OSM < /C>文件中提取所有数据，通过<强> < />（一个快速灵活的C++库来处理OpenStudioMeta数据），然后用<强> < /强>：< /P>处理它。
代码：
import xml.etree.cElementTree as ET
osm_file = "ahmedabad_india.osm"

for event, elem in ET.iterparse(osm_file, events=("start",)):
     print(elem)
     # prints the Element 'osm' at 0x03A7DC08>
     #<Element 'bounds' at 0x03A7DDA0>
     #<Element 'node' at 0x03A7DE90>
     #<Element 'tag' at 0x03A7DF08> and so on ...

import osmium as osm
import pandas as pd

class OSMHandler(osm.SimpleHandler):
    def __init__(self):
        osm.SimpleHandler.__init__(self)
        self.osm_data = []

    def tag_inventory(self, elem, elem_type):
        for tag in elem.tags:
            self.osm_data.append([elem_type, 
                                   elem.id, 
                                   elem.version,
                                   elem.visible,
                                   pd.Timestamp(elem.timestamp),
                                   elem.uid,
                                   elem.user,
                                   elem.changeset,
                                   len(elem.tags),
                                   tag.k, 
                                   tag.v])

    def node(self, n):
        self.tag_inventory(n, "node")

    def way(self, w):
        self.tag_inventory(w, "way")

    def relation(self, r):
        self.tag_inventory(r, "relation")


osmhandler = OSMHandler()
# scan the input file and fills the handler list accordingly
osmhandler.apply_file("muenchen.osm")

# transform the list into a pandas DataFrame
data_colnames = ['type', 'id', 'version', 'visible', 'ts', 'uid',
                 'user', 'chgset', 'ntags', 'tagkey', 'tagvalue']
df_osm = pd.DataFrame(osmhandler.osm_data, columns=data_colnames)
df_osm = tag_genome.sort_values(by=['type', 'id', 'ts'])

输出：

import xml.etree.cElementTree as ET
osm_file = "ahmedabad_india.osm"

for event, elem in ET.iterparse(osm_file, events=("start",)):
     print(elem)
     # prints the Element 'osm' at 0x03A7DC08>
     #<Element 'bounds' at 0x03A7DDA0>
     #<Element 'node' at 0x03A7DE90>
     #<Element 'tag' at 0x03A7DF08> and so on ...

import osmium as osm
import pandas as pd

class OSMHandler(osm.SimpleHandler):
    def __init__(self):
        osm.SimpleHandler.__init__(self)
        self.osm_data = []

    def tag_inventory(self, elem, elem_type):
        for tag in elem.tags:
            self.osm_data.append([elem_type, 
                                   elem.id, 
                                   elem.version,
                                   elem.visible,
                                   pd.Timestamp(elem.timestamp),
                                   elem.uid,
                                   elem.user,
                                   elem.changeset,
                                   len(elem.tags),
                                   tag.k, 
                                   tag.v])

    def node(self, n):
        self.tag_inventory(n, "node")

    def way(self, w):
        self.tag_inventory(w, "way")

    def relation(self, r):
        self.tag_inventory(r, "relation")


osmhandler = OSMHandler()
# scan the input file and fills the handler list accordingly
osmhandler.apply_file("muenchen.osm")

# transform the list into a pandas DataFrame
data_colnames = ['type', 'id', 'version', 'visible', 'ts', 'uid',
                 'user', 'chgset', 'ntags', 'tagkey', 'tagvalue']
df_osm = pd.DataFrame(osmhandler.osm_data, columns=data_colnames)
df_osm = tag_genome.sort_values(by=['type', 'id', 'ts'])

我首先关心的是如何获取.osm文件。有没有一种自动化的pythonic方法来获取这样的文件？此外，在访问数据的过程中，是否不必下载一些消耗系统资源的物理文件就可以直接访问数据？您只需访问osm网站，选择一个小区域并将其导出。如何获取元素的纬度和经度？@VictorMarconi如果您编写print（elem）在tag_库存定义下方，您可以看到坐标的存储方式如下
location=8.786805/53.074942
，这意味着elem.location将为您提供该值