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Examples

Inflation over time (NZ CPI)

from vswarehouse import Client

client = Client("vs_your_key")
df = client.statsnz("nz_cpi", start="2010-01-01")
df.plot_series()

library(vswarehouse)

vs_key("vs_your_key")
vs_get_statsnz("nz_cpi", start = "2010-01-01") |> vs_plot()

Compare multiple series

import pandas as pd
import matplotlib.pyplot as plt

client = Client("vs_your_key")

cpi  = client.statsnz("nz_cpi",          start="2015-01-01")
unem = client.oecd("nz_unemployment",     start="2015-01-01")

fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 6), sharex=True)
cpi.plot_series(ax=ax1)
unem.plot_series(ax=ax2)
plt.tight_layout()
plt.show()

library(ggplot2)
library(patchwork)
library(vswarehouse)

vs_key("vs_your_key")

p1 <- vs_get_statsnz("nz_cpi",       start = "2015-01-01") |> vs_plot()
p2 <- vs_get_oecd("nz_unemployment", start = "2015-01-01") |> vs_plot()

p1 / p2   # stacked with patchwork

Discover and filter series

# All Stats NZ series
statsnz = client.list("Stats NZ")

# All OECD series
oecd = client.list("OECD")

print(f"Stats NZ: {len(statsnz)} series, OECD: {len(oecd)} series")

# Source-specific list helpers
statsnz <- vs_list_statsnz()
oecd    <- vs_list_oecd()
tsy     <- vs_list_treasury()

cat("Stats NZ:", nrow(statsnz), "series\n")
cat("OECD:",     nrow(oecd),    "series\n")
cat("Treasury:", nrow(tsy),     "series\n")

Government fiscal data

spending <- client.treasury("treasury_fiscal_spending", start="2000-01-01")
debt     <- client.treasury("treasury_fiscal_debt",     start="2000-01-01")

spending.plot_series()

spending <- vs_get_treasury("treasury_fiscal_spending", start = "2000-01-01")
debt     <- vs_get_treasury("treasury_fiscal_debt",     start = "2000-01-01")

vs_plot(spending)

Export to CSV

df = client.statsnz("nz_cpi", start="2020-01-01")
df.to_csv("nz_cpi.csv", index=False)

df <- vs_get_statsnz("nz_cpi", start = "2020-01-01")
write.csv(df, "nz_cpi.csv", row.names = FALSE)

Notebook-friendly caching

# cache=True means repeated runs don't re-hit the API
client = Client(cache=True)

df = client.statsnz("nz_cpi")   # fetched once
df = client.statsnz("nz_cpi")   # from cache

# In R Markdown, wrap in a chunk with cache=TRUE

```{r load-data, cache=TRUE}
library(vswarehouse)
vs_key(Sys.getenv("VS_API_KEY"))
df <- vs_get_statsnz("nz_cpi", start = "2015-01-01")
```

In R Markdown / Quarto

---
title: "NZ Economic Overview"
---

```{r setup, include=FALSE}
library(vswarehouse)
library(ggplot2)
vs_key(Sys.getenv("VS_API_KEY"))
```

```{r cpi, fig.cap="NZ Consumer Price Index since 2010"}
vs_get_statsnz("nz_cpi", start = "2010-01-01") |>
  vs_plot() +
  labs(y = "Index (base 1000)")
```

```{r unemployment, fig.cap="NZ Unemployment Rate"}
vs_get_oecd("nz_unemployment", start = "2010-01-01") |>
  vs_plot() +
  labs(y = "Rate (%)")
```