matplotlib difficult to show all x tick labels

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)