![]() update_xaxes ( showgrid = True, ticklabelmode = "period" ) fig. Bar ( name = "Middle-aligned", x = df, y = df, xperiod = "M1", xperiodalignment = "middle" )) fig. Scatter ( name = "End-aligned", mode = "markers+lines", x = df, y = df, xperiod = "M1", xperiodalignment = "end" )) fig. Scatter ( name = "Middle-aligned", mode = "markers+lines", x = df, y = df, xperiod = "M1", xperiodalignment = "middle" )) fig. ![]() Scatter ( name = "Start-aligned", mode = "markers+lines", x = df, y = df, xperiod = "M1", xperiodalignment = "start" )) fig. Scatter ( name = "Raw Data", mode = "markers+lines", x = df, y = df, marker_symbol = "star" )) fig. DataFrame ( dict ( date =, value = )) fig = go. Import aph_objects as go import pandas as pd df = pd. Make a list of dates and convert them in datetime format as x. Note that by default, the formatting of values of X and Y values in the hover label matches that of the tick labels of the corresponding axes, so when customizing the tick labels to something broad like "month", it's usually necessary to customize the hover label to something narrower like the actual date, as below. To plot data against specific dates on the X-axis using matplotlib, we can take the following steps Set the figure size and adjust the padding between and around the subplots. ![]() To have the year number appear on every tick label, '' should be used instead of '\n'. This attribute also accepts a number of milliseconds, which can be scaled up to days by multiplying by 24*60*60*1000.ĭate axis tick labels have the special property that any portion after the first instance of '\n' in tickformat will appear on a second line only once per unique value, as with the year numbers in the example below. The dtick attribute controls the spacing between gridlines, and the "M1" setting means "1 month". Tick labels can be formatted using the tickformat attribute (which accepts the d3 time-format formatting strings) to display only the month and year, but they still represent an instant by default, so in the figure below, the text of the label "Feb 2018" spans part of the month of January and part of the month of February. The one I most commonly use is here Share Improve this answer Follow answered at 22:26 Paul H 64. import matplotlib.pyplot as plt import matplotlib.ticker. 145 In short: import matplotlib.dates as mdates myFmt mdates.DateFormatter ('d') ax.tmajorformatter (myFmt) Many examples on the matplotlib website. By default, the tick labels (and optional ticks) are associated with a specific grid-line, and represent an instant in time, for example, "00:00 on February 1, 2018". If you set the index to the datetime series by converting the dates with pd.todatetime (.), matplotlib will handle the x axis for you. Applying this formatting object to the major tick marks on the x-axis with tmajorformatter().
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