From 9f01f50f52e16cca6849dff5419f6bfa8e1574e3 Mon Sep 17 00:00:00 2001 From: Anubhav Jain Date: Thu, 11 Jul 2019 15:54:37 -0700 Subject: [PATCH] Update README.md clarify installation --- README.md | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 0f43c09..bc8a912 100644 --- a/README.md +++ b/README.md @@ -8,6 +8,10 @@ Installation is easy with pip pip install pvcz ``` +Note that you should make sure you have: +- pandas (v0.24.2 or higher to ensure that the ``pickle`` serialization used by this package works as intended) +- For plotting, you will need to install matplotlib BaseMap (https://matplotlib.org/basemap/users/installing.html#installation) + # About The data is calcuated from the global land data accumulation service (GLDAS) at 0.25 degree resolution across the world. @@ -41,7 +45,7 @@ The following code snippet shows how to find the climate stressors and zones clo ```python import pvcz -# Note df is a flattened list of lat/lon values that only includes those over land +# Note df is a flattened pandas.DataFrame of lat/lon values that only includes those over land df = pvcz.get_pvcz_data() # Point of interest specified by lat/lon coordinates. @@ -102,4 +106,4 @@ cbar.set_label('Equivalent Temperature, Rack (C)') plt.show() ``` - \ No newline at end of file +