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refactor pandas df.append to pd.concat w/ asserts #3690

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Merged
nicolaskruchten merged 4 commits into from
May 2, 2022
Merged

refactor pandas df.append to pd.concat w/ asserts #3690

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80471f8
refactor pandas df.append to pd.concat w/ asserts
Apr 23, 2022
4660998
remove asserts from pd.concat refactoring
Apr 23, 2022
0f155ec
refactor pandas df.append to pd.concat in _core
Apr 23, 2022
5da2df7
remove assert from pd.concat refactoring in _core
Apr 24, 2022
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2 changes: 1 addition & 1 deletion packages/python/plotly/plotly/express/_core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1634,7 +1634,7 @@ def aggfunc_continuous(x):
df_tree["parent"] = df_tree["parent"].str.rstrip("/")
if cols:
df_tree[cols] = dfg[cols]
df_all_trees = df_all_trees.append(df_tree, ignore_index=True)
df_all_trees = pd.concat([df_all_trees, df_tree], ignore_index=True)

# we want to make sure than (?) is the first color of the sequence
if args["color"] and discrete_color:
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10 changes: 5 additions & 5 deletions packages/python/plotly/plotly/figure_factory/_county_choropleth.py
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Original file line number Diff line number Diff line change
Expand Up @@ -86,7 +86,7 @@ def _create_us_counties_df(st_to_state_name_dict, state_to_st_dict):
columns=["State", "ST", "geometry", "FIPS", "STATEFP", "NAME"],
index=[max(gdf.index) + 1],
)
gdf = gdf.append(singlerow, sort=True)
gdf = pd.concat([gdf, singlerow], sort=True)

f = 51515
singlerow = pd.DataFrame(
Expand All @@ -103,7 +103,7 @@ def _create_us_counties_df(st_to_state_name_dict, state_to_st_dict):
columns=["State", "ST", "geometry", "FIPS", "STATEFP", "NAME"],
index=[max(gdf.index) + 1],
)
gdf = gdf.append(singlerow, sort=True)
gdf = pd.concat([gdf, singlerow], sort=True)

f = 2270
singlerow = pd.DataFrame(
Expand All @@ -120,19 +120,19 @@ def _create_us_counties_df(st_to_state_name_dict, state_to_st_dict):
columns=["State", "ST", "geometry", "FIPS", "STATEFP", "NAME"],
index=[max(gdf.index) + 1],
)
gdf = gdf.append(singlerow, sort=True)
gdf = pd.concat([gdf, singlerow], sort=True)

row_2198 = gdf[gdf["FIPS"] == 2198]
row_2198.index = [max(gdf.index) + 1]
row_2198.loc[row_2198.index[0], "FIPS"] = 2201
row_2198.loc[row_2198.index[0], "STATEFP"] = "02"
gdf = gdf.append(row_2198, sort=True)
gdf = pd.concat([gdf, row_2198], sort=True)

row_2105 = gdf[gdf["FIPS"] == 2105]
row_2105.index = [max(gdf.index) + 1]
row_2105.loc[row_2105.index[0], "FIPS"] = 2232
row_2105.loc[row_2105.index[0], "STATEFP"] = "02"
gdf = gdf.append(row_2105, sort=True)
gdf = pd.concat([gdf, row_2105], sort=True)
gdf = gdf.rename(columns={"NAME": "COUNTY_NAME"})

gdf_reduced = gdf[["FIPS", "STATEFP", "COUNTY_NAME", "geometry"]]
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