问题
I have this plot but I need the y axis to be fixed to 00:00, 01:00, 02:00, etc all the way up to 12:00. As of now it's only plotting the values I have in the csv on the y axis. the csv is in the following format. How do o get the y axis to be constant and only show 00:00 to 12:00 in 1 hr increments and still have the data plotted correctly?
ML INT 0.1 534.15 0:00
ML EXT 0.25 654.23 3:00
ML INT 0.35 743.12 6:30
And the following is the code I have so far.
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
data = pd.read_csv('data.csv', header=None)
ints = data[data[1]=='INT']
exts = data[data[1]=='EXT']
INT_index = data[data[1]=='INT'].index
EXT_index = data[data[1]=='EXT'].index
time = [t for t in data[4]]
int_dist = [d for d in ints[3]]
ext_dist = [d for d in exts[3]]
fig, ax = plt.subplots()
ax.scatter(int_dist, INT_index, c='orange', s=150)
ax.scatter(ext_dist, EXT_index, c='black', s=150)
ax.set_yticks(np.arange(len(data[4])))
ax.set_yticklabels(time)
plt.legend(['INT', 'EXT'], loc=4)
plt.xlabel('Distance')
plt.ylabel('Time')
plt.show()
回答1:
I generated a few more rows of data to make the problem, at least on my end, a bit more meaningful.
What solved this for me was generating a 5th column (in code, not the csv) which is the number of minutes corresponding to a particular o'clock time, i.e. 11:59 maps to 719 min. Using pandas I inserted this new column into the dataframe. I could then place string ticklabels for every hour ('0:00', '1:00', etc.) at every 60 min.
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
data = pd.read_csv('Workbook2.csv', header=None)
print data
Prints my faked data:
0 1 2 3 4
0 ML INT 0.10 534.15 0:00
1 ML EXT 0.25 654.23 3:00
2 ML INT 0.30 743.12 6:30
3 ML EXT 0.35 744.20 4:30
4 ML INT 0.45 811.47 7:00
5 ML EXT 0.55 777.90 5:45
6 ML INT 0.66 854.70 7:54
7 ML EXT 0.74 798.40 6:55
8 ML INT 0.87 947.30 11:59
Now make a function to convert o'clock to minutes:
def convert_to_min(o_clock):
h, m = o_clock.split(':')
return int(h) * 60 + int(m)
# using this function create a list times in minutes for each time in col 4
min_col = [convert_to_min(t) for t in data[4]]
data[5] = min_col # inserts this list as a new column '5'
print data
Our new data:
0 1 2 3 4 5
0 ML INT 0.10 534.15 0:00 0
1 ML EXT 0.25 654.23 3:00 180
2 ML INT 0.30 743.12 6:30 390
3 ML EXT 0.35 744.20 4:30 270
4 ML INT 0.45 811.47 7:00 420
5 ML EXT 0.55 777.90 5:45 345
6 ML INT 0.66 854.70 7:54 474
7 ML EXT 0.74 798.40 6:55 415
8 ML INT 0.87 947.30 11:59 719
Now build the x and y axis data, the ticklabels, and the tick locations:
INTs = data[data[1]=='INT']
EXTs = data[data[1]=='EXT']
int_dist = INTs[3] # x-axis data for INT
ext_dist = EXTs[3]
# plotting time as minutes in range [0 720]
int_time = INTs[5] # y-axis data for INT
ext_time = EXTs[5]
time = ['0:00', '1:00', '2:00', '3:00', '4:00', '5:00',
'6:00', '7:00', '8:00', '9:00', '10:00', '11:00', '12:00']
# this will place the strings above at every 60 min
tick_location = [t*60 for t in range(13)]
Now plot:
fig, ax = plt.subplots()
ax.scatter(int_dist, int_time, c='orange', s=150)
ax.scatter(ext_dist, ext_time, c='black', s=150)
ax.set_yticks(tick_location)
ax.set_yticklabels(time)
plt.legend(['INT', 'EXT'], loc=4)
plt.xlabel('Distance')
plt.ylabel('Time')
plt.title('Seems to work...')
plt.show()
回答2:
The ticks will be a lot smarter if you use a datetime
for the y-axis.
Fake data:
df = pd.DataFrame({'value':[530,640,710], 'time':['0:00', '3:00', '6:30']})
time value
0 0:00 530
1 3:00 640
2 6:30 710
Convert df.time
from str
to datetime
:
time2 = pd.to_datetime(df.time, format='%H:%M')
plt.plot(df.value, time2, marker='o', linestyle='None')
Can't seem to get this into a scatter
instead of plot
in case it matters for you (I suppressed the line). Maybe because datetime
should always be in a timeseries lineplot and never in a scatterplot (I welcome comments that let me know if this is indeed the case and datetime
cannot be put into a scatter
).
来源:https://stackoverflow.com/questions/30227591/fixed-y-axis-in-python-plotting-times-in-12-hr-format