Why Does My Pyecharts Map Lose Colors? The Hidden numpy.int64 Issue Explained

Hello everyone, I am a Python intermediate learner.

Preface

In a recent Python group chat, a fan asked a seemingly simple but actually tricky question about visualizing data with Pyecharts. The problem involved generating two datasets— datas and datas2 —that appeared identical, yet the resulting HTML maps looked very different.

Approach

The original code reads an Excel file, creates the two datasets, and renders a map:

import pandas as pd
from pyecharts import options as opts
from pyecharts.charts import Map
import operator as op
import time

df_tb = pd.read_excel('./data.xlsx')

locations = [location for location in df_tb['地区']]
values = [value for value in df_tb['2016年']]
datas = list(zip(locations, values))

map = (
    Map()
        .add('gdp', [location for location in datas], 'china')
        .set_global_opts(
            title_opts=opts.TitleOpts(title='各省贫困县分布图'),
            visualmap_opts=opts.VisualMapOpts(max_=150)
        )
)
map.render('各省贫困县分布图.html')

The map generated from datas displays colors and data values, while the map from datas2 appears without colors or data.

Conversely, the map generated from datas2 shows no colors or data:

Solution

Inspecting the two datasets reveals that the numbers in datas are of type int, while those in datas2 are of type numpy.int64. The numpy.int64 type cannot be rendered in the HTML map, causing the visual discrepancy.

Converting the numpy.int64 values to plain int resolves the issue. The corrected function is:

def func(m):
    a = []
    for i in range(0, 35):
        b = (df_tb['地区'][i], int(df_tb[m][i]))
        a.append(b)
    return a

After applying this change and re‑running the program, the map displays correctly with colors and data:

Conclusion

This article demonstrates how a subtle data type mismatch—using numpy.int64 instead of int —can break Pyecharts visualizations, and provides a simple casting fix to ensure accurate map rendering.