Humanities Data Analysis “125 85018 Karsdrop Humanities ch01 3p” — 2020/8/19 — 11 01 — page 149 — #24 Processing Tabular Data • 149 Figure 4 4 Visualization of the moving average turnover (window is 2[.]
“125-85018_Karsdrop_Humanities_ch01_3p” — 2020/8/19 — 11:01 — page 149 — #24 Processing Tabular Data Figure 4.4 Visualization of the moving average turnover (window is 25 years) for boy names boy_rm = boy_turnover.rolling(25).mean() ax = boy_rm.plot(title="Moving average turnover (boys; window = 25)") ax.set_ylabel("Absolute turnover") The rolling average visualization of boy turnovers in figure 4.3 suggests that there is a similar acceleration Our analysis thus seems to provide additional evidence for Lieberson’s (2000) claim that the rate of change in the leading names given to children has increased over the past two centuries In what follows, we will have a closer look at how the practice of naming children in the United States has changed over the course of the past two centuries 4.3 Changing Naming Practices In the previous section, we identified a rapid acceleration of the rate of change in the leading names given to children in the United States In this section, we shed light on some specific changes the naming practice has undergone, and also on some intriguing patterns of change We will work our way through three small case studies, and demonstrate some of the more advanced functionality of the Pandas library along the way • 149