How do I fix this type error ('value' must be an instance of str or bytes, not a float) on Python

Question

I want to plot a graph for Covid-19 in India and so far there's no problem when I manually input my data as x and y axis. But since the data is quite long and when I want to read it as .csv file, it gives me this error 'value' must be an instance of str or bytes, not a float. I have also try to wrap int(corona_case), but giving me another new error, cannot convert the series to <class 'int'. Also I would be very appreciate if someone can suggest me tutorials on plotting graph involving datetime using python since this is my first time learning python. I am using Python 3.

p/s I seem can't find a way to share my csv file so I am gonna leave it in snippet.

import pandas as pd
from datetime import datetime, timedelta
from matplotlib import pyplot as plt
from matplotlib import dates as mpl_dates
import numpy as np

plt.style.use('seaborn')

data = pd.read_csv('india.csv')
corona_date = data['Date']
corona_case = data['Case']
 
plt.plot_date (corona_date, corona_case, linestyle='solid')

plt.gcf().autofmt_xdate()

plt.title('COVID-19 in India')
plt.xlabel('Date')
plt.ylabel('Cumulative Case')

plt.tight_layout()

plt.show()

Date,Case
2020-09-30,6225763
2020-10-01,6312584
2020-10-02,6394068
2020-10-03,6473544
2020-10-04,6549373
2020-10-05,6623815
2020-10-06,6685082

Solution

convert all DataFrame columns to the int64 dtype

df = df.astype(int)

convert column "a" to int64 dtype and "b" to complex type

`df = df.astype({"a": int, "b": complex})` 

convert Series to float16 type

s = s.astype(np.float16) 

convert Series to Python strings

s = s.astype(str)

convert Series to categorical type - see docs for more details

s = s.astype('category')

Comments

[Siti]

Hi, I have seen and tried this one too before, this too, would give me an error, ValueError: invalid literal for int() with base 10: '\t'

[Hasnat]

that means there are non number characters in the case column in this case a tab('\t'). You can try removing these characters. pd.to_numeric(data['case'], error='coerce') which converts number values in string to numbers and non-numeric values to null then remove null values data.dropna(subset=['case']).

[Siti]

I've tried that, but still giving me a value error. I think there must be something wrong with my column date, as I put non number characters 2020-01-30 ValueError: invalid literal for int() with base 10: '2020-01-30'.

[Siti]

I have also add these 2 lines, but still giving me the same error. date_format = mpl_dates.DateFormatter('%b, %d, %Y') plt.gca().xaxis.set_major_formatter(date_format)

[Hasnat]

Pandas reads datetime in string format from csv. You can convert it to datetime as data['Date'] = pd.to_datetime(data['Date']) and that works with matplotlib. It would be better if you can share the csv.