I have a geopandas dataframe, which consists of the region name(District), the geometry column, and the amount column. My goal is to plot a choropleth map using the method mentioned below
https://plotly.com/python/choropleth-maps/#using-geopandas-data-frames
Here’s a snippet of my dataframe
I also checked that my columns were in the right format/type.
And here's the code I used to plot the map
fig = px.choropleth(merged,
geojson=merged.geometry,
locations=merged.index,
color="Amount")
fig.update_geos(fitbounds="locations", visible=False)
fig.show()
It produced the below figure
which is obviously not the right figure. For some reasons, it doesn't show the map, instead it shows a line and when I zoom in, I am able to see the map but it has lines running through it. Like this
Has anyone ran into a similar problem? If so how were you able to resolve it?
The Plotly version I am using is 4.7.0. I have tried upgrading to a most recent version but it still didn’t work.
Any help is greatly appreciated. Please find my code and the data on my github.
I'll give you the answer to #tgrandje's comment that solved the problem. Thanks to #Poopah and #tgrandje for the opportunity to raise the answer.
import pandas as pd
import plotly.express as px
import geopandas as gpd
import pyproj
# reading in the shapefile
fp = "./data/"
map_df = gpd.read_file(fp)
map_df.to_crs(pyproj.CRS.from_epsg(4326), inplace=True)
df = pd.read_csv("./data/loans_amount.csv")
# join the geodataframe with the cleaned up csv dataframe
merged = map_df.set_index('District').join(df.set_index('District'))
#merged = merged.reset_index()
merged.head()
fig = px.choropleth(merged, geojson=merged.geometry, locations=merged.index, color="Amount")
fig.update_geos(fitbounds="locations", visible=False)
fig.show()
Another possible source of the problem (when using Plotly graph_objects) is mentioned in this answer over at gis.stackexchange.com:
The locations argument has to point to a column that matches GeoJSON's 'id's.
The geojson argument expects a dictionary.
To solve your problem, you should: (i) point locations to the dataframe's index, and (ii) turn your GeoJSON string to a dictionary.
It's not exactly the answer to your question, but I thought my problem was the same as yours and this helped me. So I am including the answer here.
Related
I know some similar questions have been asked but none have been able to answer my question or maybe my python programming skills are not that great(they are not). Ultimately I'm trying to creating a table to look like the one below, all of the "Some values" will be filled with JSON data which I do know how to import but creating the table to then export it to a PDF using FPDF is what is stumping me. I've tried pretty table and wasn't able to achieve this I tried using html but really I dont know too much html to build a table from scratch like this. so if some one could help or point in the right direction it would be appreciated.
I would recommend the using both the Pandas Library and MatplotLib
Firstly, with Pandas you can load data in from a JSON, either from a JSON file or string with the read_json(..) function documented here.
Something like:
import pandas as pd
df = pd.read_json("/path/to/my/file.json")
There is plenty of functionality withing the pandas library to manipulate your dataframe (your table) however you need.
Once you're done, you can then use MatplotLib to generate your PDF without needing any HTML
This would then become something like
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
df = pd.read_json("/path/to/my/file.json")
# Manipulate your dataframe 'df' here as required.
# Now use Matplotlib to write to a PDF
# Lets create a figure first
fig, ax = plt.subplots(figsize=(20, 10))
ax.axis('off')
the_table = ax.table(
cellText=df.values,
colLabels=df.columns,
loc='center'
)
# Now lets create the PDF and write the table to it
pdf_pages = PdfPages("/path/to/new/table.pdf")
pdf_pages.savefig(fig)
pdf_pages.close()
Hope this helps.
I have a dataframe of emails that has three columns: From, Message and Received (which is a date format).
I've written the below script to show how many messages there are per month in a bar plot.
But the plot doesn't show and I can't work out why, it's no doubt very simple. Any help understanding why is much appreciated!
Thanks!
import pandas as pd
import matplotlib.pyplot as plt
df = pd.read_csv('XXX')
df = df[df['Message'].notna()]
df['Received'] = pd.to_datetime(df['Received'], format='%d/%m/%Y')
df['Received'].groupby(df['Received'].dt.month).count().plot
A pyplot object (commonly plt) is not shown until you call plt.show(). It is designed that way so you can create your plot and then modify it as needed before showing or saving.
Also checkout plt.savefig().
First off, I'd like to start by saying that I am asking this question since I do not believe that it is related to the similarly titled question: plotly choropleth not plotting data, as I believe it has something to do with the custom GEOJSON boundaries and/or how I am accessing the data.
I use the crime.csv table from https://www.kaggle.com/ankkur13/boston-crime-data, and I am using a GEOJSON file from Boston Analytics (Fetched in the script). Currently, my code runs without errors, but it does not load the data onto the plot.
import pandas as pd
import plotly.graph_objs as go
from urllib.request import urlopen
import json
# Read Dataset
# Located at: https://www.kaggle.com/ankkur13/boston-crime-data
df = pd.read_csv("crime.csv")
with urlopen('http://bostonopendata-boston.opendata.arcgis.com/datasets/9a3a8c427add450eaf45a470245680fc_5.geojson?outSR={%22latestWkid%22:2249,%22wkid%22:102686}') as response:
pd_districts = json.load(response)
df_agg = df.groupby("DISTRICT").agg(CRIMES=("YEAR","count"))
df_agg.reset_index(inplace=True)
df_agg = df_agg[df_agg['DISTRICT'] != 'nan']
df['DISTRICT'] = df['DISTRICT'].apply(lambda x: str(x))
fig = go.Figure(go.Choroplethmapbox(geojson=pd_districts,
locations=df_agg['DISTRICT'].unique(),
z=df_agg['CRIMES'],
featureidkey="features.properties.DISTRICT")
)
fig.update_layout(mapbox_style="carto-positron")
fig.update_geos(fitbounds="locations")
fig.show()
I believe it has something to do with my featureidkey. However, I have tried multiple variants such as properties.DISTRICT, properties.ID, but to no avail.
I also ran a few sanity checks to make sure that the data was accessible, and here they are:
print(df_agg['DISTRICT'].unique())
print(pd_districts['features'][0]['properties']['ID'])
print(df['DISTRICT'].dtype)
Any help would be appreciated.
I want the x axis tick marks to be the different states ie. IDLE, Data=Addr, Hammer, etc that are in column A of the csv file.
import pandas as pd
import matplotlib.pyplot as plt
df1 = pd.read_csv("Output.csv", index_col = 0)
df1.plot(x = df1.index.values)
I have also tried
df1.plot(xticks = df1.index.values)
without any success.
CSV File
Plot
Thanks in advance!
You may want to try Seaborn because it looks like it is not a plotting issue but rather peripheral styling issue (all blacked out) in your environment.
Once you installed Seaborn, insert a piece of code below to yours.
import seaborn as sns
sns.set_style("whitegrid")
As a side note, if you wish to align the number of ticks in x axis to that of labels you have, replace your plotting part with the following:
df1.plot()
plt.xticks(range(df1.shape[0]), df1.index)
Hope this helps.
What i am trying to do is slightly basic, however i am very new to python, and am having trouble.
Goal: is to plot the yellow highlighted Row(which i have highlighted, however it will not be highlighted when i need to read the data) on the Y-Axis and plot the "Time" Column on the X-Axis.
Here is a photo of the Data, and then the code that i have tried along with its error.
Code
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib import style
style.use('ggplot')
#Reading CSV and converting it to a df(Data_Frame)
df1 = pd.read_csv('Test_Sheet_1.csv', skiprows = 8)
#Creating a list from df1 and labeling it 'Time'
Time = df1['Time']
print(Time)
#Reading CSV and converting it to a df(Data_Frame)
df2 = pd.read_csv('Test_Sheet_1.csv').T
#From here i need to know how to skip 4 lines.
#I need to skip 4 lines AFTER the transposition and then we can plot DID and
Time
DID = df2['Parameters']
print(DID)
Error
As you can see from the code, right now i am just trying to print the Data so that i can see it, and then i would like to put it onto a graph.
I think i need to use the 'skiplines' function after the transposition, so that python can know where to read the "column" labeled parameters(its only a column after the Transposition), However i do not know how to use the skip lines function after the transposition unless i transpose it to a new Excel Document, but this is not an option.
Any help is very much appreciated,
Thank you!
Update
This is the output I get when I add print(df2.columns.tolist())