<jupyter_start><jupyter_text>[![image](https://colab.research.google.com/assets/colab-badge.svg)](https://githubtocolab.com/giswqs/leafmap/blob/master/examples/notebooks/09_csv_to_points.ipynb)[![image](https://binder.pangeo.io/badge_logo.svg)](https://gishub.org/leafmap-pangeo)Uncomment the following line to install [leafmap](https://leafmap.org) if needed.<jupyter_code># !pip install leafmap

import os
import leafmap.leafmap as leafmap

#leafmap.update_package()

in_csv_1 = 'https://raw.githubusercontent.com/Niko-La/jupyter_equity_2020/main/world_cities.csv'
in_csv_2 = 'https://raw.githubusercontent.com/Niko-La/jupyter_equity_2020/main/GISLAKE%20-%20Sheet%201.csv'

df = leafmap.csv_to_pandas(in_csv_2)
of = leafmap.csv_to_pandas(in_csv_1)
of


df.dropna(subset = ['longitude'], inplace=True)
df = df.reset_index(drop=True)
df

df = df.loc[:, ['ID','latitude','longitude']]
df
Map = leafmap.Map()
Map.add_xy_data(in_csv_1, x="longitude", y="latitude", layer_name="World")
Map
leafmap.split_map(left_layer="Esri.WorldTopoMap", right_layer="OpenTopoMap")
out_geojson = os.path.join(out_dir, 'world_cities.geojson')
leafmap.csv_to_geojson(in_csv, out_geojson)
# gdf = leafmap.csv_to_gdf(in_csv)
# gdf<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1608730800323363, 'fraction_numerical': 0.01778496362166532, 'mean_word_length': 7.47945205479452, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 7, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '236251', 'license': 'MIT', 'n_tokens_mistral': 528, 'n_tokens_neox': 509, 'n_words': 55, 'path': 'examples/notebooks/X - GISLake .ipynb', 'repo_name': 'Niko-La/leafmap', 'size': '1237'}