Hello Community,
Can anyone help me with this please. I want to create an OrderedDict from a csv file and use it to populate pages.
Hello @wilson_uzziel,
You can use pandas to load .csv files, process data the way you want, and display the result by using st.write.
Out of curiosity, why do you want to use OrderedDict instead of regular python dict ?
Hello @okld,
You the reason i need to use OrderedDict is that it will enable population of pages based on selected results from selectbox. For example i have a csv file which contains GDP data from this data i want a page generated once the use choose a country from the selectbox. Then, thereafter filter data based on the choice
Is there a way of working out this without using OrderedDict. Please help
As of Python 3.6 (using CPython implementation), regular dicts keep the insertion order like OrderedDict. And since 3.7, python specification enforced this behavior for all python implementations.
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Thank @okld,
At the moment, am in desperate situation of working out this right. I sincerely request you help even if it means using python dict i will appreciate.
Hi @wilson_uzziel -
I do need to ask you to be patient with users on this message board; people are trying to help you, but we cannot guarantee that we can answer your question on a specific timeframe.
As @okld has indicated, the solution to do this is possible and unrelated to Streamlit. You will likely get a lot more help if you can give us a code snippet of what you’ve tried, and ask how to solve a particular issue. Telling us “I want to use OrderedDict” doesn’t give us much to work with.
Best,
Randy
As @randyzwitch said, without more info, we may not help you the way you want.
However, just to give you an example of what you can do, here is a generic code snippet to display a DataFrame, and filter columns. I used this dataset for my tests. You’ll notice that I didn’t use any dict or OrderedDict at all.
import pandas as pd
import streamlit as st
def main():
st.sidebar.title("GDP reader")
df = load_csv("gdp.csv")
for column in df.columns:
options = pd.Series(["All"]).append(df[column], ignore_index=True).unique()
choice = st.sidebar.selectbox("Select {}.".format(column), options)
if choice != "All":
df = df[df[column] == choice].drop(columns=column)
st.table(df)
@st.cache
def load_csv(path):
return pd.read_csv(path)
if __name__ == "__main__":
main()
2 Likes
@randyzwitch @okld, I am sorry for my impatience.
I like to say i have tried out the script though I am get an error on for column in df.columns:
@wilson_uzziel I’m sorry but I won’t be able to help with so few information. What error do you have? Have you tested my code with the dataset I linked or with yours?
Well, the error is self-explanatory. You have an indentation error: ensure you don’t have any additional space or tab at the beginning of this line.