Tick labels on a pandas datetime axis are not aligned with the ticks

Question

I've successfully created the code to generate a bunch of charts. However, the x axis labels are slightly offset (to the left) from the x axis tick marks.

Dataframe

  stationId       date variable  value  prefix uom
0    site 1 2016-04-07       pH   6.90     NaN  pH
1    site 1 2016-07-11       pH   6.80     NaN  pH
2    site 1 2017-10-09       pH   6.80     NaN  pH
3    site 1 2017-10-09       pH   6.80     NaN  pH
4    site 1 2016-06-29       pH   6.79     NaN  pH

There is nothing in the code which i can see why this should happen.

    #plot
for line,group in linedf.groupby(['variable']):
    x = group['date']
    ax1 = group.plot(x='date', figsize=(8.2,4.5),linestyle='--',
                     linewidth=0.75,rot=0,marker='o',markersize=3)
    
    #set axis labels and chart title
    plt.title("chartTitle", fontsize=12)
    ax1.set_xlabel('Date', fontsize=10)
    ax1.set_ylabel('GWL (mAHD)',fontsize=10)

    #set text font
    rcParams['font.family'] = 'serif'
    rcParams['font.serif'] = ['Cambria']

    #set dates for x tick labels
    years = mdates.YearLocator()   # every year
    months = mdates.MonthLocator()  # every month
    yearsFmt = mdates.DateFormatter('%Y')


    lgd = plt.legend(bbox_to_anchor=(0.0 ,-0.13, 1.0, -0.03), 
                     loc=2,ncol = 6, mode="expand", borderaxespad=0.0,shadow=True)
            
    plt.show()

Full dataframe here

Selected columns below incase the link dies

stationId,date,variable,value
site 1,2016-07-04,pH,6.9
site 1,2016-11-07,pH,6.8
site 1,2017-09-10,pH,6.8
site 1,2016-06-29,pH,6.79
site 1,2016-03-14,pH,6.7
site 1,2016-07-25,pH,6.7
site 1,2016-04-20,pH,6.6
site 1,2016-08-08,pH,6.6
site 1,2018-06-08,pH,6.6
site 1,2018-08-20,pH,6.6
site 1,2018-11-26,pH,6.6
site 1,2018-10-12,pH,6.6
site 1,2016-05-16,pH,6.5
site 1,2016-06-14,pH,6.5
site 1,2016-08-24,pH,6.5
site 1,2016-05-09,pH,6.5
site 1,2016-09-20,pH,6.5
site 1,2016-11-14,pH,6.5
site 1,2016-12-14,pH,6.5
site 1,2017-05-01,pH,6.5
site 1,2017-01-18,pH,6.5
site 1,2017-12-04,pH,6.5
site 1,2017-06-19,pH,6.5
site 1,2017-03-07,pH,6.5
site 1,2017-08-14,pH,6.5
site 1,2017-09-15,pH,6.5
site 1,2017-09-25,pH,6.5
site 1,2017-11-12,pH,6.5
site 1,2018-04-16,pH,6.5
site 1,2018-05-14,pH,6.5
site 1,2018-05-28,pH,6.5
site 1,2018-06-13,pH,6.5
site 1,2018-09-07,pH,6.5
site 1,2018-05-09,pH,6.5
site 1,2018-09-17,pH,6.5
site 1,2018-03-10,pH,6.5
site 1,2018-10-31,pH,6.5
site 1,2018-12-11,pH,6.5
site 1,2016-12-01,pH,6.4
site 1,2016-05-31,pH,6.4
site 1,2016-04-10,pH,6.4
site 1,2016-10-17,pH,6.4
site 1,2017-01-31,pH,6.4
site 1,2017-02-16,pH,6.4
site 1,2017-02-03,pH,6.4
site 1,2017-03-15,pH,6.4
site 1,2017-03-29,pH,6.4
site 1,2017-08-05,pH,6.4
site 1,2017-05-22,pH,6.4
site 1,2017-07-19,pH,6.4
site 1,2017-02-08,pH,6.4
site 1,2017-08-29,pH,6.4
site 1,2017-11-13,pH,6.4
site 1,2018-01-22,pH,6.4
site 1,2018-05-02,pH,6.4
site 1,2018-02-19,pH,6.4
site 1,2018-03-19,pH,6.4
site 1,2018-06-25,pH,6.4
site 1,2016-02-18,pH,6.3
site 1,2016-02-03,pH,6.3
site 1,2016-05-05,pH,6.3
site 1,2016-03-02,pH,6.2
site 2,2016-06-29,pH,7.29
site 2,2017-02-08,pH,6.9
site 2,2017-09-15,pH,6.9
site 2,2016-05-31,pH,6.8
site 2,2017-02-16,pH,6.8
site 2,2017-09-25,pH,6.8
site 2,2017-09-10,pH,6.8
site 2,2016-06-14,pH,6.7
site 2,2016-08-24,pH,6.7
site 3,2018-09-07,pH,6.9
site 3,2018-08-20,pH,6.9
site 3,2018-07-23,pH,6.8
site 4,2016-06-29,pH,7.3
site 4,2016-07-25,pH,7.2
site 4,2016-11-07,pH,7.1
site 4,2017-09-15,pH,7.1
site 4,2016-06-14,pH,7.0
site 4,2017-08-14,pH,7.0
site 4,2017-09-25,pH,7.0
site 4,2018-06-04,pH,7.0
site 4,2018-09-07,pH,7.0
site 4,2018-10-31,pH,7.0
site 4,2018-10-12,pH,7.0
site 4,2016-05-16,pH,6.9
site 4,2017-05-01,pH,6.9
site 4,2017-12-04,pH,6.9
site 4,2017-05-22,pH,6.9
site 4,2017-06-19,pH,6.9
site 4,2017-03-07,pH,6.9
site 4,2017-02-08,pH,6.9
site 4,2017-08-29,pH,6.9
site 4,2017-11-12,pH,6.9
site 4,2018-02-01,pH,6.9
site 4,2018-04-30,pH,6.9
site 4,2018-05-28,pH,6.9
site 4,2018-06-13,pH,6.9
site 4,2018-06-08,pH,6.9
site 4,2018-03-10,pH,6.9
site 4,2018-12-11,pH,6.9
site 4,2018-11-26,pH,6.9
site 4,2016-04-20,pH,6.8
site 4,2016-08-08,pH,6.8
site 4,2016-08-24,pH,6.8
site 4,2016-10-17,pH,6.8
site 4,2016-04-11,pH,6.8
site 4,2016-11-14,pH,6.8
site 4,2017-01-31,pH,6.8
site 4,2017-02-16,pH,6.8
site 4,2017-02-03,pH,6.8
site 4,2017-03-29,pH,6.8
site 4,2017-08-05,pH,6.8
site 4,2017-05-06,pH,6.8
site 4,2017-07-19,pH,6.8
site 4,2017-09-10,pH,6.8
site 4,2017-10-31,pH,6.8
site 4,2017-11-13,pH,6.8
site 4,2017-11-27,pH,6.8
site 4,2018-01-22,pH,6.8
site 4,2018-02-19,pH,6.8
site 4,2018-05-03,pH,6.8
site 4,2018-04-16,pH,6.8
site 4,2018-05-14,pH,6.8
site 4,2018-06-25,pH,6.8
site 4,2018-07-23,pH,6.8
site 4,2018-08-20,pH,6.8
site 4,2018-09-17,pH,6.8
site 4,2018-10-15,pH,6.8
site 4,2016-12-01,pH,6.7
site 4,2016-02-18,pH,6.7
site 4,2016-02-03,pH,6.7
site 4,2016-03-14,pH,6.7
site 4,2016-07-04,pH,6.7
site 4,2016-05-31,pH,6.7
site 4,2016-05-09,pH,6.7
site 4,2016-09-20,pH,6.7
site 4,2016-04-10,pH,6.7
site 4,2016-12-14,pH,6.7
site 4,2017-01-18,pH,6.7
site 4,2018-05-02,pH,6.7
site 4,2018-03-19,pH,6.7
site 4,2018-05-09,pH,6.7
site 4,2016-03-02,pH,6.6
site 4,2016-05-05,pH,6.5
site 5,2016-02-03,pH,7.0
site 5,2017-01-31,pH,7.0
site 5,2017-02-16,pH,6.9
site 6,2016-06-29,pH,7.56
site 6,2016-08-08,pH,7.4
site 6,2018-02-01,pH,7.2
site 6,2018-06-08,pH,7.2
site 6,2018-03-10,pH,7.2
site 6,2018-10-15,pH,7.2
site 6,2016-05-09,pH,7.1
site 6,2016-04-11,pH,7.1
site 6,2017-12-04,pH,7.1
site 6,2017-03-07,pH,7.1
site 6,2017-02-08,pH,7.1
site 6,2017-09-15,pH,7.1
site 6,2017-11-12,pH,7.1
site 6,2018-05-28,pH,7.1
site 6,2018-09-07,pH,7.1
site 6,2018-07-23,pH,7.1
site 6,2016-04-20,pH,7.0
site 6,2017-05-06,pH,7.0
site 6,2017-06-19,pH,7.0
site 6,2017-07-19,pH,7.0
site 6,2017-08-14,pH,7.0
site 6,2017-08-29,pH,7.0
site 6,2017-09-25,pH,7.0
site 6,2017-10-31,pH,7.0
site 6,2017-11-13,pH,7.0
site 6,2017-11-27,pH,7.0
site 6,2018-01-22,pH,7.0
site 6,2018-02-19,pH,7.0
site 6,2018-06-04,pH,7.0
site 6,2018-10-31,pH,7.0
site 6,2018-11-26,pH,7.0
site 6,2018-10-12,pH,7.0
site 6,2017-05-22,pH,6.9
site 6,2017-09-10,pH,6.9
site 6,2018-05-02,pH,6.9
site 6,2018-05-03,pH,6.9
site 6,2018-03-19,pH,6.9
site 6,2018-04-16,pH,6.9
site 6,2018-04-30,pH,6.9
site 6,2018-05-14,pH,6.9
site 6,2018-06-13,pH,6.9
site 6,2018-06-25,pH,6.9
site 6,2018-08-20,pH,6.9
site 6,2018-05-09,pH,6.9
site 6,2018-09-17,pH,6.9
site 7,2016-06-29,pH,7.94
site 7,2016-04-20,pH,7.8
site 7,2016-05-16,pH,7.8
site 7,2016-11-07,pH,7.8
site 7,2016-05-09,pH,7.7
site 7,2016-12-01,pH,7.6
site 7,2016-03-02,pH,7.6
site 7,2016-05-05,pH,7.6
site 7,2016-07-25,pH,7.6
site 7,2016-08-24,pH,7.6
site 7,2016-04-10,pH,7.6
site 7,2016-10-17,pH,7.6
site 7,2017-02-03,pH,7.6
site 7,2017-02-16,pH,7.5
site 7,2017-03-15,pH,7.5
site 7,2018-08-20,pH,7.5
site 7,2016-02-18,pH,7.4
site 7,2016-07-04,pH,7.4
site 7,2016-05-31,pH,7.4
site 7,2016-06-14,pH,7.4
site 7,2016-09-20,pH,7.4
site 7,2016-04-11,pH,7.4
site 7,2017-01-18,pH,7.4
site 7,2017-01-31,pH,7.4
site 7,2017-11-12,pH,7.4
site 7,2018-03-19,pH,7.4
site 7,2018-05-28,pH,7.4
site 7,2018-06-25,pH,7.4
site 7,2018-06-08,pH,7.4
site 7,2018-05-09,pH,7.4
site 7,2018-12-11,pH,7.4
site 7,2018-11-26,pH,7.4
site 7,2018-10-12,pH,7.4
site 7,2016-08-08,pH,7.3
site 7,2016-12-14,pH,7.3
site 7,2017-05-01,pH,7.3
site 7,2017-02-08,pH,7.3
site 7,2017-09-15,pH,7.3
site 7,2017-09-25,pH,7.3
site 7,2017-11-27,pH,7.3
site 7,2018-06-13,pH,7.3
site 7,2018-09-07,pH,7.3
site 7,2018-10-15,pH,7.3
site 7,2018-10-31,pH,7.3
site 7,2016-02-03,pH,7.2
site 7,2016-11-14,pH,7.2
site 7,2017-03-07,pH,7.2
site 7,2017-08-14,pH,7.2
site 7,2017-08-29,pH,7.2
site 7,2017-10-31,pH,7.2
site 7,2017-11-13,pH,7.2
site 7,2018-02-01,pH,7.2
site 7,2018-02-19,pH,7.2
site 7,2018-07-23,pH,7.2
site 7,2018-09-17,pH,7.2
site 7,2018-03-10,pH,7.2
site 7,2017-12-04,pH,7.1
site 7,2018-05-03,pH,7.1
site 7,2017-05-22,pH,7.0
site 7,2017-05-06,pH,7.0
site 7,2017-08-05,pH,6.9
site 7,2017-06-19,pH,6.9
site 7,2016-03-14,pH,6.7
site 7,2017-09-10,pH,6.7
site 8,2016-11-07,pH,7.6
site 8,2018-05-28,pH,7.2
site 8,2016-03-02,pH,7.1
site 8,2017-05-01,pH,7.1
site 8,2017-08-05,pH,7.1
site 8,2016-04-20,pH,7.0
site 8,2017-01-18,pH,7.0
site 8,2017-01-31,pH,7.0
site 8,2017-02-03,pH,7.0
site 8,2017-09-10,pH,7.0
site 8,2018-06-04,pH,7.0
site 8,2018-06-13,pH,7.0
site 8,2018-09-07,pH,7.0
site 8,2018-12-11,pH,7.0
site 8,2016-05-16,pH,6.9
site 8,2018-02-19,pH,6.9
site 8,2018-03-10,pH,6.9
site 8,2016-12-01,pH,6.8
site 8,2016-02-18,pH,6.8
site 8,2016-10-17,pH,6.8
site 8,2017-06-19,pH,6.8

score 3 · Accepted Answer · answered Feb 19 '19 at 06:55

Without seeing the dataframe you are using (or at least a chunk of it) I have to speculate a bit, but it should suffice to simply adjust the alignment of the tick labels manually using

for tick in ax1.xaxis.get_major_ticks():
    tick.label1.set_horizontalalignment('center')

Without the dataframe I can't test to ensure this works in your case, but from the plot in the question it appears the alignment of the x-tick labels has been set to 'right' and setting them to 'center' will align them how you desire.

Drawn from the centered ticklabels example in the matplotlib docs.

Trenton McKinney · Answer 2 · 2023-05-27T21:06:18.470

This option is from a comment by ImportanceOfBeingErnest:
- plt.setp(ax.get_xticklabels(), ha="center")
- This occurs because pandas manipulates the tick parameters a bit.
Tested in python 3.11.3, pandas 2.0.1, matplotlib 3.7.1

import pandas as pd
import matplotlib.pyplot as plt

data = {'stationId': ['site1', 'site1', 'site1', 'site1', 'site1', 'site2', 'site2', 'site2', 'site2', 'site2'],
        'date': ['2016-04-07', '2016-07-11', '2017-10-09', '2017-10-12', '2016-06-29', '2016-04-07', '2016-07-11', '2017-10-09', '2017-10-12', '2016-06-29'],
        'variable': ['pH', 'pH', 'pH', 'pH', 'pH', 'pH', 'pH', 'pH', 'pH', 'pH'],
        'value': [6.9, 6.8, 6.8, 6.8, 6.79, 5.9, 5.8, 5.8, 5.8, 5.79]}
df = pd.DataFrame(data)

# convert to datetime; format= is not required, but it is faster if specified
df.date = pd.to_datetime(df.date, format='%Y-%m-%d')

# reshape the dataframe to plot each site
ph = df[df.variable.eq('pH')].pivot(index='date', columns='stationId', values='value')

# plot
ax = ph.plot(rot=0, figsize=(12, 5))

# center the labels
_ = plt.setp(ax.get_xticklabels(), ha="center")

score 0 · Answer 3 · edited Jun 30 '23 at 16:13

The datetime xticks are right aligned because the 'date' column in the OP, and in the small sample in this answer, are datetime64[ns] Dtype.
- set(tick.label1.get_horizontalalignment() for tick in ax.xaxis.get_major_ticks()) shows the alignment.
- df.date[0] → Timestamp('2016-07-04 00:00:00')
- This occurs with df.date = pd.to_datetime(df.date, format='%d/%m/%Y')
  - Specifying the format= option is irrelevant to this issue.
Since the data does not actually contain a time component, use df.date = pd.to_datetime(df.date, format='%d/%m/%Y').dt.date
- df.date[0] → datetime.date(2016, 7, 4)
- This change results in 'center' aligned xtick labels.
The datetime tick labels are formatted differently depending on the range in the data.
Tested in python 3.11.3, pandas 2.0.1, matplotlib 3.7.1

import pandas as pd

# using the csv data at the bottom of the OP
df = pd.read_csv('test.csv')

# convert the date column
df.date = pd.to_datetime(df.date, format='%Y-%m-%d').dt.date

# reshape the dataframe to plot each site
ph = df[df.variable.eq('pH')].pivot(index='date', columns='stationId', values='value')

# plot
ax = ph.plot(rot=0, figsize=(12, 5), linestyle='--', linewidth=0.75, marker='o', markersize=3)

# move the legend
_ = ax.legend(bbox_to_anchor=(1, 0.5), loc='center left', frameon=False)

Note the date xtick labels are center aligned without any additional formatting.

Tick labels on a pandas datetime axis are not aligned with the ticks

3 Answers3

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