Question

我有一个如下所示结构的数据框。我想计算年增长率。问题是并非所有型号的时间步长都相同。在下面的示例中，REMIND以5年为间隔提供数据，而TIAM-ECN以10年为间隔提供数据。

model     scenario  region  year  value
REMIND    Base  NORTH_AM    2010  314.1330
REMIND    Base    CHINA+    2010  1325.9220
REMIND    RefPol  NORTH_AM  2010  314.1330
REMIND    RefPol  CHINA+    2010  1325.9220
TIAM-ECN  Base    NORTH_AM  2010  344.4005
TIAM-ECN  Base    CHINA+    2010  1341.3352
TIAM-ECN  RefPol  NORTH_AM  2010  344.4005
TIAM-ECN  RefPol  CHINA+    2010  1341.3352
REMIND    Base    NORTH_AM  2015  327.6270
REMIND    Base    CHINA+    2015  1354.3180
REMIND    RefPol  NORTH_AM  2015  327.6270
REMIND    RefPol  CHINA+    2015  1354.3180
REMIND    Base    NORTH_AM  2020  340.8490
REMIND    Base    CHINA+    2020  1372.4630
REMIND    RefPol  NORTH_AM  2020  340.8490
REMIND    RefPol  CHINA+    2020  1372.4630
TIAM-ECN  Base    NORTH_AM  2020  374.2647
TIAM-ECN  Base    CHINA+    2020  1387.7915
TIAM-ECN  RefPol  NORTH_AM  2020  374.2647
TIAM-ECN  RefPol  CHINA+    2020  1387.7915

计算不同区间的增长率很简单：

library(dplyr)

tmp_gr <- group_by(df, model, scenario, region) %>%
  mutate(value = value / lag(value) - 1) %>%
  ungroup()

收益率（我遗漏了2010年的NA）：

model     scenario region   year    value
REMIND    Base     NORTH_AM 2015    -0.7557456
REMIND    Base     CHINA+   2015    3.1337191
REMIND    RefPol   NORTH_AM 2015    -0.7580871
REMIND    RefPol   CHINA+   2015    3.1337191
REMIND    Base     NORTH_AM 2020    -0.7483242
REMIND    Base     CHINA+   2020    3.0266012
REMIND    RefPol   NORTH_AM 2020    -0.7516516
REMIND    RefPol   CHINA+   2020    3.0266012
TIAM-ECN  Base     NORTH_AM 2020    -0.7273044
TIAM-ECN  Base     CHINA+   2020    2.7080483
TIAM-ECN  RefPol   NORTH_AM 2020    -0.7303164
TIAM-ECN  RefPol   CHINA+   2020    2.7080483

但是现在，通过将区间增长率除以区间长度来计算年增长率

tmp_gr_yearly <- group_by(df, model, scenario, region) %>%
  mutate(value = (value / lag(value) - 1) / (year - lag(year))) %>%
  ungroup()

的产率：

model     scenario region   year   value
REMIND    Base     NORTH_AM 2015    -0.1511491
REMIND    Base     CHINA+   2015    Inf
REMIND    RefPol   NORTH_AM 2015    -Inf
REMIND    RefPol   CHINA+   2015    Inf
REMIND    Base     NORTH_AM 2020    -0.1496648
REMIND    Base     CHINA+   2020    Inf
REMIND    RefPol   NORTH_AM 2020    -Inf
REMIND    RefPol   CHINA+   2020    Inf
TIAM-ECN  Base     NORTH_AM 2020    -Inf
TIAM-ECN  Base     CHINA+   2020    Inf
TIAM-ECN  RefPol   NORTH_AM 2020    -Inf
TIAM-ECN  RefPol   CHINA+   2020    Inf

我不明白Inf的来源。

有什么想法吗？

Answer 1

我计算简单，非标准化增长率的例子已经错了。

无论如何，我想我自己想出来了：

tmp_gr <- group_by(df, model, scenario, region) %>%
  mutate(value = lag(value, n=0, order_by=year) / lag(value, order_by=year) - 1) %>%
  ungroup()

 tmp_gr_yearly <- group_by(df, model, scenario, region) %>%
   mutate(value = (lag(value, n=0, order_by=year) / lag(value, order_by=year) - 1) / (lag(year, n=0, order_by=year) - lag(year, order_by=year))) %>%
 ungroup()

通过对所有值使用lag-operator并明确告知顺序，整个事物对非有序数据变得健壮。

R计算不同区间长度的年度或标准化增长率

1 个答案: