import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from datetime import datetime as dt
import csv

file = "2017-09-04-data.csv"
f = open(file,"r")
reader = csv.reader(f)

time_d = []
temp = []
humid = []

for row in reader:
    date = dt.strptime(row[0], "%Y/%m/%d %H:%M:%S")
    time_d.append(date.strftime("%H:%M"))
    temp.append(row[1])
    humid.append(row[2])
f.close()

time_d = pd.to_datetime(time_d)
fig = plt.figure()
ax = fig.add_subplot(1,1,1)
ax.plot(time_d, temp)

days = mdates.AutoDateLocator()
daysFmt = mdates.DateFormatter("%H:%M")
ax.xaxis.set_major_locator(days)
ax.xaxis.set_major_formatter(daysFmt)
plt.show()

f7c15886741720b0f16c38a9a6d3600b8bc765e7
<mask token>

<mask token>
for row in reader:
    date = dt.strptime(row[0], '%Y/%m/%d %H:%M:%S')
    time_d.append(date.strftime('%H:%M'))
    temp.append(row[1])
    humid.append(row[2])
f.close()
<mask token>
ax.plot(time_d, temp)
<mask token>
ax.xaxis.set_major_locator(days)
ax.xaxis.set_major_formatter(daysFmt)
plt.show()

<mask token>
file = '2017-09-04-data.csv'
f = open(file, 'r')
reader = csv.reader(f)
time_d = []
temp = []
humid = []
for row in reader:
    date = dt.strptime(row[0], '%Y/%m/%d %H:%M:%S')
    time_d.append(date.strftime('%H:%M'))
    temp.append(row[1])
    humid.append(row[2])
f.close()
time_d = pd.to_datetime(time_d)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.plot(time_d, temp)
days = mdates.AutoDateLocator()
daysFmt = mdates.DateFormatter('%H:%M')
ax.xaxis.set_major_locator(days)
ax.xaxis.set_major_formatter(daysFmt)
plt.show()

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from datetime import datetime as dt
import csv
file = '2017-09-04-data.csv'
f = open(file, 'r')
reader = csv.reader(f)
time_d = []
temp = []
humid = []
for row in reader:
    date = dt.strptime(row[0], '%Y/%m/%d %H:%M:%S')
    time_d.append(date.strftime('%H:%M'))
    temp.append(row[1])
    humid.append(row[2])
f.close()
time_d = pd.to_datetime(time_d)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.plot(time_d, temp)
days = mdates.AutoDateLocator()
daysFmt = mdates.DateFormatter('%H:%M')
ax.xaxis.set_major_locator(days)
ax.xaxis.set_major_formatter(daysFmt)
plt.show()

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from datetime import datetime as dt
import csv

file = "2017-09-04-data.csv"
f = open(file,"r")
reader = csv.reader(f)

time_d = []
temp = []
humid = []

for row in reader:
    date = dt.strptime(row[0], "%Y/%m/%d %H:%M:%S")
    time_d.append(date.strftime("%H:%M"))
    temp.append(row[1])
    humid.append(row[2])
f.close()

time_d = pd.to_datetime(time_d)
fig = plt.figure()
ax = fig.add_subplot(1,1,1)
ax.plot(time_d, temp)

days = mdates.AutoDateLocator()
daysFmt = mdates.DateFormatter("%H:%M")
ax.xaxis.set_major_locator(days)
ax.xaxis.set_major_formatter(daysFmt)
plt.show()
