ValueError: year is out of range using matplotlib.pyplot - python-3.x

Question

After I call candlestick_ohlc, I can't seem to convert the x axis dates to something matplotlib can understand.
I'm a noob Python programmer. I've tried turning the dataframe into a list, I've tried passing dates to candlestick_ohlc, nothing seems to work other than changing
df['time'] = (df['time'].astype('float'))
into
df['time'] = (df['time'].astype('float')\1000)
Although that renders the wrong datetime.
import requests
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as mdate
import matplotlib.style as style
import matplotlib.ticker as mticker
from matplotlib.dates import date2num
from mpl_finance import candlestick_ohlc
import datetime as dt
import numpy as np
import matplotlib.ticker as mticker
def get_data(date):
""" Query the API for 2000 days historical price data starting from "date". """
url = "https://min-api.cryptocompare.com/data/histoday?fsym=BTC&tsym=USD&limit=2000&toTs={}".format(date)
r = requests.get(url)
ipdata = r.json()
return ipdata
def get_df(from_date, to_date):
""" Get historical price data between two dates. """
date = to_date
holder = []
# While the earliest date returned is later than the earliest date requested, keep on querying the API
# and adding the results to a list.
while date > from_date:
data = get_data(date)
holder.append(pd.DataFrame(data['Data']))
date = data['TimeFrom']
# Join together all of the API queries in the list.
df = pd.concat(holder, axis = 0)
# Remove data points from before from_date
df = df[df['time']>from_date]
# Convert to timestamp to readable date format
# df['time'] = pd.to_datetime(df['time'], unit='s')
# Make the DataFrame index the time
df.set_index('time', inplace=True)
# And sort it so its in time order
df.sort_index(ascending=False, inplace=True)
return df
df = get_df(1528502400, 1560112385)
style.use('dark_background')
fig = plt.figure()
ax1 = plt.subplot2grid((1,1), (0,0))
df = df.reset_index()
cols = ['time', 'open', 'high', 'low', 'close', 'volumefrom', 'volumeto']
df = df[cols]
#IF YOU /1000 AFER ('float') IT WILL RUN BUT NOT CORRECT DATE
df['time'] = (df['time'].astype('float'))
print(df.dtypes)
ohlc = df.values.tolist()
candlestick_ohlc(ax1, ohlc, width=.4, colorup='g', colordown='r')
# IF YOU COMMENT NEXT 4 LINES IT WILL RUN, but NO DATES for XAXIS
date_fmt = "%d-%m-%Y"
date_formatter = mdate.DateFormatter(date_fmt)
ax1.xaxis.set_major_formatter(date_formatter)
fig.autofmt_xdate()
ax1.set_ylabel('BTC Price (USD)')
ax1.set_xlabel('Date')
plt.show()
Expected result would be date labels plotted as d-m-y. :)
Wish this had dates for xaxis labels not seconds since 1970
This is what I want it to look like, but with accurate dates

Answer 1

This is how to fix the code:
df['time'] = df['time'].apply(mdates.epoch2num)
It was definitely one of those lines of code that you spend hours on... now I know.