Related
i'm working on something based of this blogpost:
https://python-visualization.github.io/folium/quickstart.html#Getting-Started
specifically part 13 - using Cloropleth maps:
the piece of code they use is the following:
import pandas as pd
url = (
"https://raw.githubusercontent.com/python-visualization/folium/master/examples/data"
)
state_geo = f"{url}/us-states.json"
state_unemployment = f"{url}/US_Unemployment_Oct2012.csv"
state_data = pd.read_csv(state_unemployment)
m = folium.Map(location=[48, -102], zoom_start=3)
folium.Choropleth(
geo_data=state_geo,
name="choropleth",
data=state_data,
columns=["State", "Unemployment"],
key_on="feature.id",
fill_color="YlGn",
fill_opacity=0.7,
line_opacity=0.2,
legend_name="Unemployment Rate (%)",
).add_to(m)
folium.LayerControl().add_to(m)
m
if I use this I get the requested map.
Now I try to do this with my own data; i work in databricks
so I have a JSON with the GEOJSON data (source_file1) and a CSV file (source_file2) with the data that needs to be "plotted" on the map.
source_file1 = "dbfs:/mnt/sandbox/MAARTEN/TOPO/Belgie_GEOJSON.JSON"
state_geo = spark.read.json(source_file1,multiLine=True)
source_file2 = "dbfs:/mnt/sandbox/MAARTEN/TOPO/DATASVZ.csv"
df_2 = spark.read.format("CSV").option("inferSchema", "true").option("header", "true").option("delimiter",";").load(source_file2)
state_data = df_2.toPandas()
when adjusting the code below:
m = folium.Map(location=[48, -102], zoom_start=3)
folium.Choropleth(
geo_data=state_geo,
name="choropleth",
data=state_data,
columns=["State", "Unemployment"],
key_on="feature.properties.name_nl",
fill_color="YlGn",
fill_opacity=0.7,
line_opacity=0.2,
legend_name="% Marktaandeel CC",
).add_to(m)
folium.LayerControl().add_to(m)
m
So i upload the geo_data parameter as a Sparkdatafram, I get the following error:
ValueError: Cannot render objects with any missing geometries: DataFrame[features: array<struct<geometry:struct<coordinates:array<array<array<string>>>,type:string>,properties:struct<arr_fr:string,arr_nis:bigint,arr_nl:string,fill:string,fill-opacity:double,name_fr:string,name_nl:string,nis:bigint,population:bigint,prov_fr:string,prov_nis:bigint,prov_nl:string,reg_fr:string,reg_nis:string,reg_nl:string,stroke:string,stroke-opacity:bigint,stroke-width:bigint>,type:string>>, type: string]```
I think it is because transforming the data from the "blob format" in the Azure datalake to the sparkdataframe, something goes wrong with the format. I tested this in a jupyter notebook from my desktop, data straight from file to folium and it all works.
If i load it directly from the source, like the example does with their webpage, so i adjust the 'geo_data' parameter for the folium function:
m = folium.Map(location=[48, -102], zoom_start=3)
folium.Choropleth(
geo_data=source_file1, #this gets adjusted directly to data lake
name="choropleth",
data=state_data,
columns=["State", "Unemployment"],
key_on="feature.properties.name_nl",
fill_color="YlGn",
fill_opacity=0.7,
line_opacity=0.2,
legend_name="% Marktaandeel CC",
).add_to(m)
folium.LayerControl().add_to(m)
m
I get the error
Use "/dbfs", not "dbfs:": The function expects a local file path. The error is caused by passing a path prefixed with "dbfs:".
So I started wondering what is the difference between my JSON file and the one of the blogpost. And the only thing i can imagine is that the Azure datalake doesn't store my json as a json but as a block blob file and for some reason i am not converting it properly so that folium can read it.
Azure blob storage (data lake)
So can someone with folium knowledge let me know if
A. it is not possible to load the geo_data directly from a datalake ?
B. in what format I need to upload the data ?
any thoughts on this would be helpfull!!!
thanks in advance!
Solved this issue, just had to replace "dbfs:" with "/dbfs". I tried it a lot of times but used "/dbfs:" and got another error.
can't believe i'm this stupid :-)
My model has a json field. I can access jsonfield['key1'] with the following query
from django.contrib.postgres.fields.jsonb import KeyTextTransform
MyModel.objects.annotate(val=KeyTextTransform('key1', 'jsonfield')).order_by('val')
But how can I access a key like jsonfield['key1']['key2'] or even more nested ones?
This can't be the only solution, right?
MyModel.objects.annotate(val=KeyTextTransform('key2', (KeyTextTransform('key1', 'jsonfield'))).order_by('val')
The hard part is already done, thankfully. KeyTextTransform is composable. All we have to do is compose it.
class NestableKeyTextTransform:
def __new__(cls, field, *path):
if not path:
raise ValueError("Path must contain at least one key.")
head, *tail = path
field = KeyTextTransform(head, field)
for head in tail:
field = KeyTextTransform(head, field)
return field
MyModel.objects.annotate(
single_nested_value=NestableKeyTextTransform(
"json_field", "query", "name"
),
array_access=NestableKeyTextTransform(
"json_field", "query", "address_line", 1
),
)
Though I would like to point out that this may be a better way to do it:
from django.db.models import F
MyModel.objects.annotate(
single_nested_value=F("json_field__query__name"),
array_access=F("json_field__query__address_line__1"),
)
NB as of the start of 2023 (in django's development version) you can now also do:
from django.db.models.fields.json import KT
Dogs.objects.annotate(
first_breed=KT("data__breed__1"),
owner_name=KT("data__owner__name")
)
See docs and feature request
I want to append multiple list items to a JSON file, but it creates a list within a list, and therefore I cannot acces the list from python. Since the code is overwriting existing data in the JSON file, there should not be any list there. I also tried it by having just an text in the file without brackets. It just creates a list within a list so [["x", "y","z"]] instead of ["x", "y","z"]
import json
filename = 'vocabulary.json'
print("Reading %s" % filename)
try:
with open(filename, "rt") as fp:
data = json.load(fp)
print("Data: %s" % data)#check
except IOError:
print("Could not read file, starting from scratch")
data = []
# Add some data
TEMPORARY_LIST = []
new_word = input("give new word: ")
TEMPORARY_LIST.append(new_word.split())
print(TEMPORARY_LIST)#check
data = TEMPORARY_LIST
print("Overwriting %s" % filename)
with open(filename, "wt") as fp:
json.dump(data, fp)
example and output with appending list with split words:
Reading vocabulary.json
Data: [['my', 'dads', 'house', 'is', 'nice']]
give new word: but my house is nicer
[['but', 'my', 'house', 'is', 'nicer']]
Overwriting vocabulary.json
So, if I understand what you are trying to accomplish correctly, it looks like you are trying to overwrite a list in a JSON file with a new list created from user input. For easiest data manipulation, set up your JSON file in dictionary form:
{
"words": [
"my",
"dad's",
"house",
"is",
"nice"
]
}
You should then set up functions to separate your functionality to make it more manageable:
def load_json(filename):
with open(filename, "r") as f:
return json.load(f)
Now, we can use those functions to load the JSON, access the words list, and overwrite it with the new word.
data = load_json("vocabulary.json")
new_word = input("Give new word: ").split()
data["words"] = new_word
write_json("vocabulary.json", data)
If the user inputs "but my house is nicer", the JSON file will look like this:
{
"words": [
"but",
"my",
"house",
"is",
"nicer"
]
}
Edit
Okay, I have a few suggestions to make before I get into solving the issue. Firstly, it's great that you have delegated much of the functionality of the program over to respective functions. However, using global variables is generally discouraged because it makes things extremely difficult to debug as any of the functions that use that variable could have mutated it by accident. To fix this, use method parameters and pass around the data accordingly. With small programs like this, you can think of the main() method as the point in which all data comes to and from. This means that the main() function will pass data to other functions and receive new or edited data back. One final recommendation, you should only be using all capital letters for variable names if they are going to be constant. For example, PI = 3.14159 is a constant, so it is conventional to make "pi" all caps.
Without using global, main() will look much cleaner:
def main():
choice = input("Do you want to start or manage the list? (start/manage)")
if choice == "start":
data = load_json()
words = data["words"]
dictee(words)
elif choice == "manage":
manage_list()
You can use the load_json() function from earlier (notice that I deleted write_json(), more on that later) if the user chooses to start the game. If the user chooses to manage the file, we can write something like this:
def manage_list():
choice = input("Do you want to add or clear the list? (add/clear)")
if choice == "add":
words_to_add = get_new_words()
add_words("vocabulary.json", words_to_add)
elif choice == "clear":
clear_words("vocabulary.json")
We get the user input first and then we can call two other functions, add_words() and clear_words():
def add_words(filename, words):
with open(filename, "r+") as f:
data = json.load(f)
data["words"].extend(words)
f.seek(0)
json.dump(data, f, indent=4)
def clear_words(filename):
with open(filename, "w+") as f:
data = {"words":[]}
json.dump(data, f, indent=4)
I did not utilize the load_json() function in the two functions above. My reasoning for this is because it would call for opening the file more times than needed, which would hurt performance. Furthermore, in these two functions, we already need to open the file, so it is okayt to load the JSON data here because it can be done with only one line: data = json.load(f). You may also notice that in add_words(), the file mode is "r+". This is the basic mode for reading and writing. "w+" is used in clear_words(), because "w+" not only opens the file for reading and writing, it overwrites the file if the file exists (that is also why we don't need to load the JSON data in clear_words()). Because we have these two functions for writing and/or overwriting data, we don't need the write_json() function that I had initially suggested.
We can then add to the list like so:
>>> Do you want to start or manage the list? (start/manage)manage
>>> Do you want to add or clear the list? (add/clear)add
>>> Please enter the words you want to add, separated by spaces: these are new words
And the JSON file becomes:
{
"words": [
"but",
"my",
"house",
"is",
"nicer",
"these",
"are",
"new",
"words"
]
}
We can then clear the list like so:
>>> Do you want to start or manage the list? (start/manage)manage
>>> Do you want to add or clear the list? (add/clear)clear
And the JSON file becomes:
{
"words": []
}
Great! Now, we implemented the ability for the user to manage the list. Let's move on to creating the functionality for the game: dictee()
You mentioned that you want to randomly select an item from a list and remove it from that list so it doesn't get asked twice. There are a multitude of ways you can accomplish this. For example, you could use random.shuffle:
def dictee(words):
correct = 0
incorrect = 0
random.shuffle(words)
for word in words:
# ask word
# evaluate response
# increment correct/incorrect
# ask if you want to play again
pass
random.shuffle randomly shuffles the list around. Then, you can iterate throught the list using for word in words: and start the game. You don't necessarily need to use random.choice here because when using random.shuffle and iterating through it, you are essentially selecting random values.
I hope this helped illustrate how powerful functions and function parameters are. They not only help you separate your code, but also make it easier to manage, understand, and write cleaner code.
Earlier I asked about gathering information from API-Link, and I have managed to get out most of the details by using the answar I got.
Now ny problem is when another API to get more information
This time the file will contain this information:
{
"username":"UserName",
"confirmed_rewards":"0",
"round_estimate":"0.00000000",
"total_hashrate":"0.000",
"payout_history":"0",
"round_shares":"0",
"workers":{
"UserName.1":{
"alive":"0",
"hashrate":"0.000"
},
"UserName.2":{
"alive":"0",
"hashrate":"0.000"
},
"UserName.3":{
"alive":"1",
"hashrate":"1517.540",
"last_share_timestamp":1369598007
},
"UserName.4":{
"alive":"0",
"hashrate":"0.000"
}
}
}
And I want to gather each of the workers and print them out. This "workers" could contain multiple information, but always start with "UserName.x", where the username come from the "username" paramter each time.
The numbers will always vary from 0 and up
I want to gether the information in the same way by accessing the document, and decode and print out all the workers, whatever the numbers of them are.
By using the script provided in my last question(look at the link in the start), i was thinking that it would be something like
local t = json.decode( txt )
print("Workers: ".. t["workers.UserName.1"])
But this was not the way.
Due to the username changing all the time, I was also thinking somthing like
print("Workers: ".. t["workers" .. "." .. "username" .. "." .. "1"])
From here I have no clue about how I should gather the information, even when the names and numbers vary
Thanks in advance
Here is the perfect solution:
local json = require "json"
local t = json.decode( jsonFile( "data.json" )
local workers = t.workers
for name, user in pairs(workers) do
print("--------------------")
print(name)
for tag, value in pairs(user) do
print(tag , value)
end
end
Here are some more info:
http://www.coronalabs.com/blog/2011/08/03/tutorial-exploring-json-usage-in-corona/
http://www.coronalabs.com/blog/2011/06/21/understanding-lua-tables-in-corona-sdk/
http://lua-users.org/wiki/TablesTutorial
BACKGROUND:
I am having issues trying to search through some CSV files.
I've gone through the python documentation: http://docs.python.org/2/library/csv.html
about the csv.DictReader(csvfile, fieldnames=None, restkey=None, restval=None, dialect='excel', *args, **kwds) object of the csv module.
My understanding is that the csv.DictReader assumes the first line/row of the file are the fieldnames, however, my csv dictionary file simply starts with "key","value" and goes on for atleast 500,000 lines.
My program will ask the user for the title (thus the key) they are looking for, and present the value (which is the 2nd column) to the screen using the print function. My problem is how to use the csv.dictreader to search for a specific key, and print its value.
Sample Data:
Below is an example of the csv file and its contents...
"Mamer","285713:13"
"Champhol","461034:2"
"Station Palais","972811:0"
So if i want to find "Station Palais" (input), my output will be 972811:0. I am able to manipulate the string and create the overall program, I just need help with the csv.dictreader.I appreciate any assistance.
EDITED PART:
import csv
def main():
with open('anchor_summary2.csv', 'rb') as file_data:
list_of_stuff = []
reader = csv.DictReader(file_data, ("title", "value"))
for i in reader:
list_of_stuff.append(i)
print list_of_stuff
main()
The documentation you linked to provides half the answer:
class csv.DictReader(csvfile, fieldnames=None, restkey=None, restval=None, dialect='excel', *args, **kwds)
[...] maps the information read into a dict whose keys are given by the optional fieldnames parameter. If the fieldnames parameter is omitted, the values in the first row of the csvfile will be used as the fieldnames.
It would seem that if the fieldnames parameter is passed, the given file will not have its first record interpreted as headers (the parameter will be used instead).
# file_data is the text of the file, not the filename
reader = csv.DictReader(file_data, ("title", "value"))
for i in reader:
list_of_stuff.append(i)
which will (apparently; I've been having trouble with it) produce the following data structure:
[{"title": "Mamer", "value": "285713:13"},
{"title": "Champhol", "value": "461034:2"},
{"title": "Station Palais", "value": "972811:0"}]
which may need to be further massaged into a title-to-value mapping by something like this:
data = {}
for i in list_of_stuff:
data[i["title"]] = i["value"]
Now just use the keys and values of data to complete your task.
And here it is as a dictionary comprehension:
data = {row["title"]: row["value"] for row in csv.DictReader(file_data, ("title", "value"))}
The currently accepted answer is fine, but there's a slightly more direct way of getting at the data. The dict() constructor in Python can take any iterable.
In addition, your code might have issues on Python 3, because Python 3's csv module expects the file to be opened in text mode, not binary mode. You can make your code compatible with 2 and 3 by using io.open instead of open.
import csv
import io
with io.open('anchor_summary2.csv', 'r', newline='', encoding='utf-8') as f:
data = dict(csv.reader(f))
print(data['Champhol'])
As a warning, if your csv file has two rows with the same value in the first column, the later value will overwrite the earlier value. (This is also true of the other posted solution.)
If your program really is only supposed to print the result, there's really no reason to build a keyed dictionary.
import csv
import io
# Python 2/3 compat
try:
input = raw_input
except NameError:
pass
def main():
# Case-insensitive & leading/trailing whitespace insensitive
user_city = input('Enter a city: ').strip().lower()
with io.open('anchor_summary2.csv', 'r', newline='', encoding='utf-8') as f:
for city, value in csv.reader(f):
if user_city == city.lower():
print(value)
break
else:
print("City not found.")
if __name __ == '__main__':
main()
The advantage of this technique is that the csv isn't loaded into memory and the data is only iterated over once. I also added a little code the calls lower on both the keys to make the match case-insensitive. Another advantage is if the city the user requests is near the top of the file, it returns almost immediately and stops looking through the file.
With all that said, if searching performance is your primary consideration, you should consider storing the data in a database.