I was trying to create a graph, but doesn’t matter which Y inputs I use, it always end looking like this straight line with a continuos slope:
This is what my code is loooking like:
import pandas as pd
import plotly.express as px
df = pd.read_csv(‘twitch.csv’ ,encoding = “ISO-8859-1”)
fig = px.line(df, x = ‘Month/year’, y = ‘Avg.concur.viewers’, title=‘Média de audiencia’)
fig.show()
Anyone can help?
Your code seems to be correct.
What does the underlying data say?
You can check it with:
df[‘Avg.concur.viewers’].describe()
The .describe() didn’t work.
Here is the csv content:
Month/year,Avg.concur.viewers,Avg.concur.channels,Time watched,Active streamers
November 2019,“1,222,247”,45.644,880M hrs,“3,198,707”
December 2019,“1,184,935”,45.633,882M hrs,“3,353,608”
January 2020 ,“1,357,375”,52.821,“1,010M hrs”,“3,935,308”
February 2020 ,“1,410,516”,53.816,982M�hrs,“3,753,539”
March 2020,“1,638,049”,66.011,“1,219M hrs”,“5,080,031”
April 2020 ,“2,488,881”,93.75,“1,792M hrs”,“7,213,644”
May 2020 ,“2,359,765”,100.364,“1,756M hrs”,“7,398,081”
June 2020,“2,262,771”,93.932,“1,629M hrs”,“7,158,730”
July 2020,“2,115,411”,95.809,“1,574M hrs”,“7,463,817”
August 2020,“2,178,080”,96.309,“1,620M hrs”,“7,709,990”
September 2020,"2,202,200 ",91.861,“1,586M�hrs”,“7,461,252”
October 2020 ,“2,385,206”,95.074,“1,774M�hrs”,“7,844,426”
November 2020,“2,487,091”,103.917,"1,790M hrs ",“8,546,985”
December 2020 ,“2,522,869”,106.845,“1,876M hrs”,“9,241,666”
January 2021 ,“2,919,533”,119.271,"2,171M hrs ",“9,894,745”
February 2021 ,“2,945,135”,122.623,“1,979M�hrs”,“9,517,967”
March 2021,“2,913,726”,116.618,“1,050M hrs”,n/a
Pls Jack I need your help, man. You are my last hope.
sry I dont have a lot of time right now.
But your problem isn’t visualization, its the format of your data.
so play a bit with the parameters iof read_csv() to get it right or just do in manually for the few rows!
I’ve done it, Jack!!! I finally figured out the problem!!! Thank you for all the help!!]
YOU ARE THE GOAT @jack2704
