[FIXED] matplotlib difficult to show all x tick labels

Issue

I have a data series

hour
0     35845
1     18921
2     14484
3     12504
4     13862
5     14958
6     23328
7     33580
8     66878
9     65291
10    61785
11    64781
12    68799
13    72486
14    83230
15    75487
16    88231
17    85383
18    75525
19    61739
20    51696
21    43215
22    38539
23    30797
dtype: int64

I want to plot the data series and show all the x tick labels, which range from 0 to 23. The code for basic plot is

import matplotlib as plt
import seaborn as sb

fig, ax = plt.subplots()
plt.title("Collision by hour")
sb.lineplot(x = df_hour.index,
            y = df_hour.values)

Which gives me a plot with only 5 x_tick labels:

I had tried:

import matplotlib.pyplot as plt
import seaborn as sb
import import matplotlib.dates as mdate

fig, ax = plt.subplots()
plt.title("Collision by hour")

locator = mdate.AutoDateLocator(minticks=12, maxticks=24)
formatter = mdate.ConciseDateFormatter(locator)
ax.xaxis.set_major_locator(locator)
ax.xaxis.set_major_formatter(formatter)

ax.plot(df_hour.index, df_hour.values)

Result with missing odd hour and extra start and end limit:

I had tried

import matplotlib.pyplot as plt
import seaborn as sb
import import matplotlib.dates as mdate

fig, ax = plt.subplots()
plt.title("Collision by hour")

hour_locator = mdate.HourLocator(interval = 1)
hour_formatter = mdate.DateFormatter("%H")

ax.xaxis.set_major_locator(hour_locator)
ax.xaxis.set_major_formatter(hour_formatter)

ax.plot(df_hour.index, df_hour.values)

Result with unreadable x_tick label:

I had tried

fig, ax = plt.subplots()
plt.title("Collision by hour")

ax.set_xticklabels(df["hour"])
ax.plot(df_hour.index, df_hour.values)

Result with only right x_tick label:

I had tried

fig, ax = plt.subplots()
plt.title("Collision by hour")

ax.set_xticklabels([0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23])
ax.plot(df_hour.index, df_hour.values)

Result with only left x_tick label:

Don't know what else can be try.

Update: The panda series was generate from the code df_hour = df.groupby("hour").size(), where df is a data frame containing a Int64 column call "hour", values range from 0 to 23. This made the data sereis had different structure ("hour" column name and no column name for the second column)

Solution

As mentioned in the comment to the question the 'trick' is to explicit set the ticks with ax.set_xticks([0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23]) what can be also done using the hour column of the dataframe ax.set_xticks(df.hour).

Below the entire code and the image of created plot:

data = [
[0   ,  35845], 
[1   ,  18921], 
[2   ,  14484], 
[3   ,  12504], 
[4   ,  13862], 
[5   ,  14958], 
[6   ,  23328], 
[7   ,  33580], 
[8   ,  66878], 
[9   ,  65291], 
[10  ,  61785], 
[11  ,  64781], 
[12  ,  68799], 
[13  ,  72486], 
[14  ,  83230], 
[15  ,  75487], 
[16  ,  88231], 
[17  ,  85383], 
[18  ,  75525], 
[19  ,  61739], 
[20  ,  51696], 
[21  ,  43215], 
[22  ,  38539], 
[23  ,  30797], ]
import pandas as pd
df = pd.DataFrame(data, columns =['hour', 'collisions'])
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
plt.title("Collision by hour")
ax.plot(df.hour, df.collisions)
# ax.set_xticks([0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23])
ax.set_xticks(df.hour)
plt.show()

giving:

Answered By - Claudio